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All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form

A

aa - Enum constant in enum class edu.cmu.tetrad.graph.EdgeTypeProbability.EdgeType
Arrow-to-arrow
ABSOLUTE - Enum constant in enum class edu.cmu.tetrad.search.CpdagParentDistancesFromTrue.DistanceType
Calculate the absolute distance between the true edge strength and the range of estimated coefficients.
absoluteValue - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Score
The absolute value.
AbstractAnnotations<T> - Class in edu.cmu.tetrad.annotation
Abstract class for annotations.
AbstractAnnotations(String, Class<T>) - Constructor for class edu.cmu.tetrad.annotation.AbstractAnnotations
Constructor.
AbstractBootstrapAlgorithm - Class in edu.cmu.tetrad.algcomparison.algorithm
This is a base class for bootstrap algorithms.
AbstractNbComponent - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
Abstract NB component.
AbstractNbComponent(double, double, NbComponent[], int[], String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Constructs a new component with the given factor, power, parents, and
AbstractVariable - Class in edu.cmu.tetrad.data
Base class for variable specifications for DataSet.
ac - Enum constant in enum class edu.cmu.tetrad.graph.EdgeTypeProbability.EdgeType
Arrow-to-circle
active() - Method in class edu.cmu.tetrad.util.DefaultTetradLoggerConfig
isActive.
active() - Method in class edu.cmu.tetrad.util.TetradLogger.EmptyConfig
isActive.
active() - Method in interface edu.cmu.tetrad.util.TetradLoggerConfig
States whether the config is active or not.
ActiveLagGraph - Class in edu.cmu.tetrad.study.gene.tetrad.gene.graph
Adds Javabean property change events so that it can be used in a MVC type architecture.
ActiveLagGraph() - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Creates new ActiveLagGraph
AD_TREE - Enum constant in enum class edu.cmu.tetrad.search.test.ChiSquareTest.CellTableType
The AD tree cell table.
add(int, DataModel) - Method in class edu.cmu.tetrad.data.DataModelList
Adds the given DataModel to the list at the given index.
add(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.Algorithms
Adds an algorithm.
add(Simulation) - Method in class edu.cmu.tetrad.algcomparison.simulation.Simulations
Adds an simulation.
add(Statistic) - Method in class edu.cmu.tetrad.algcomparison.statistic.Statistics
Adds a statistic.
add(IndependenceFact) - Method in class edu.cmu.tetrad.data.IndependenceFacts
add.
add(OutputStream, Level) - Method in class edu.cmu.tetrad.util.LogUtils
Adds the given stream to logging.
ADD - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move.Type
Add an edge.
ADD_COLLIDER - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move.Type
Add a collider.
ADD_ORIGINAL_DATASET - Static variable in class edu.cmu.tetrad.util.Params
Constant ADD_ORIGINAL_DATASET="addOriginalDataset"
addAll(SepsetMap) - Method in class edu.cmu.tetrad.search.utils.SepsetMap
Adds all entries in the given sepset map to the current one.
addAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Adds an ambiguous triple to the list of ambiguous triples.
addAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
addAmbiguousTriple.
addAmbiguousTriple(Node, Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
addAmbiguousTriple.
addAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
addAmbiguousTriple.
addAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
addAmbiguousTriple.
addAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds an ambiguous triple to the list of ambiguous triples.
addAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Underlines
addAmbiguousTriple.
addAttribute(String, Object) - Method in class edu.cmu.tetrad.data.ContinuousVariable
addAttribute.
addAttribute(String, Object) - Method in class edu.cmu.tetrad.data.DiscreteVariable
addAttribute.
addAttribute(String, Object) - Method in class edu.cmu.tetrad.graph.Dag
Adds an attribute to the graph.
addAttribute(String, Object) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
addAttribute.
addAttribute(String, Object) - Method in interface edu.cmu.tetrad.graph.Graph
addAttribute.
addAttribute(String, Object) - Method in class edu.cmu.tetrad.graph.GraphNode
addAttribute.
addAttribute(String, Object) - Method in class edu.cmu.tetrad.graph.LagGraph
addAttribute.
addAttribute(String, Object) - Method in interface edu.cmu.tetrad.graph.Node
addAttribute.
addAttribute(String, Object) - Method in class edu.cmu.tetrad.graph.SemGraph
addAttribute.
addAttribute(String, Object) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds a key-value pair to the attributes map.
addBidirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Adds a bidirectional edge between two nodes.
addBidirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Adds a bidirected edges <-> to the graph.
addBidirectedEdge(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Adds a bidirected edges <-> to the graph.
addBidirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Adds a bidirected edges <-> to the graph.
addBidirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Adds a bidirected edges <-> to the graph.
addBidirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds a bidirected edge between two nodes.
addCategory(int, int) - Method in class edu.cmu.tetrad.bayes.Proposition
addCategory.
addCollider(Triple) - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Add another collider operation to the GraphChange.
addConditioningVariable(String, double, double) - Method in class edu.cmu.tetrad.data.Histogram
Adds a continuous conditioning variables, conditioning on a range of values.
addConditioningVariable(String, int) - Method in class edu.cmu.tetrad.data.Histogram
Adds a discrete conditioning variable, conditioning on a particular value.
addCounts(int, int, int) - Method in class edu.cmu.tetrad.bayes.CptMapCounts
Adds the specified count to the cell count at the given row and column.
addDirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Adds a directed edge between two nodes.
addDirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Adds a directed edge --> to the graph.
addDirectedEdge(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Adds a directed edge --> to the graph.
addDirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Adds a directed edge --> to the graph.
addDirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Adds a directed edge --> to the graph.
addDirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds a directed edge between two nodes to the graph.
addDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Adds a dotted underline triple to the graph.
addDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
addDottedUnderlineTriple.
addDottedUnderlineTriple(Node, Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
addDottedUnderlineTriple.
addDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
addDottedUnderlineTriple.
addDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
addDottedUnderlineTriple.
addDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds a triple with dotted underline to the list of triples.
addDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Underlines
addDottedUnderlineTriple.
addEdge(Edge) - Method in class edu.cmu.tetrad.graph.Dag
Adds a directed edge to the Directed Acyclic Graph (DAG).
addEdge(Edge) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Adds the specified edge to the graph, provided it is not already in the graph.
addEdge(Edge) - Method in interface edu.cmu.tetrad.graph.Graph
Adds the specified edge to the graph, provided it is not already in the graph.
addEdge(Edge) - Method in class edu.cmu.tetrad.graph.LagGraph
Adds the specified edge to the graph, provided it is not already in the graph.
addEdge(Edge) - Method in class edu.cmu.tetrad.graph.SemGraph
Adds the specified edge to the graph, provided it is not already in the graph.
addEdge(Edge) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds a directed edge to the graph.
addEdge(String, LaggedFactor) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Adds an edge to the given factor at lag 0 from the specified lagged factor.
addEdge(String, LaggedFactor) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Adds an edge to the given factor at lag 0 from the specified lagged factor.
addEdge(String, LaggedFactor) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Adds an edge to the given factor at lag 0 from the specified lagged factor.
addEdge(String, LaggedFactor) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Adds an edge to the given factor at lag 0 from the specified lagged factor.
addEdgeSpecializationMarkup(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Adds markups for edge specializations for the edges in the given graph.
addEdgeTypeProbability(EdgeTypeProbability) - Method in class edu.cmu.tetrad.graph.Edge
addEdgeTypeProbability.
adDep() - Method in record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Returns the value of the adDep record component.
addFactor(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Adds a factor to the graph.
addFactor(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Adds a factor to the graph.
addFactor(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Adds a factor to the graph.
addFactor(String) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Adds a factor to the graph.
addFactors(String, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Returns a string representation of the graph, indicating for each factor which lagged factors map into it.
addFactors(String, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Returns a string representation of the graph, indicating for each factor which lagged factors map into it.
addFactors(String, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Returns a string representation of the graph, indicating for each factor which lagged factors map into it.
addFactors(String, int) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Returns a string representation of the graph, indicating for each factor which lagged factors map into it.
addForbiddenReverseEdgesForDirectedEdges(Graph, Knowledge) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Adds forbidden reverse edges for directed edges in the given graph based on the knowledge.
addIndex(DataSet) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
Creates new time series dataset from the given one with index variable (e.g., time)
addKnowledgeGroup(KnowledgeGroup) - Method in class edu.cmu.tetrad.data.Knowledge
Adds a knowledge group.
addMissingData(DataSet, double[]) - Static method in class edu.cmu.tetrad.data.DataTransforms
Adds missing data values to cases in accordance with probabilities specified in a double array which has as many elements as there are columns in the input dataset.
addNode(Node) - Method in class edu.cmu.tetrad.graph.Dag
Adds a Node to the graph.
addNode(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Adds a node to the graph.
addNode(Node) - Method in interface edu.cmu.tetrad.graph.Graph
Adds a node to the graph.
addNode(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Adds a node to the graph.
addNode(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Adds a node to the graph.
addNode(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds a node to the graph.
addNonCollider(Triple) - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Add another non-collider operation to the GraphChange.
addNondirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Adds a nondirected edge between two nodes in the graph.
addNondirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Adds a nondirected edges o-o to the graph.
addNondirectedEdge(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Adds a nondirected edges o-o to the graph.
addNondirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Adds a nondirected edges o-o to the graph.
addNondirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Adds a nondirected edges o-o to the graph.
addNondirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds a nondirected edge between two nodes.
addObserver(ModelObserver) - Method in class edu.cmu.tetrad.search.MarkovCheck
Adds a ModelObserver to the list of observers.
addOrient(Node, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Add another orient operation to the GraphChange.
addOutputStream(OutputStream) - Method in class edu.cmu.tetrad.util.TetradLogger
Sets the OutputStream that is used to log matters out to.
addParent(NbComponent, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Returns the parents of this component.
addParent(NbComponent, int) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbComponent
Returns the parents of this component.
addPartiallyOrientedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Adds a partially oriented edge between two nodes.
addPartiallyOrientedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Adds a partially oriented edge o-> to the graph.
addPartiallyOrientedEdge(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Adds a partially oriented edge o-> to the graph.
addPartiallyOrientedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Adds a partially oriented edge o-> to the graph.
addPartiallyOrientedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Adds a partially oriented edge o-> to the graph.
addPartiallyOrientedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds a partially oriented edge between two given nodes.
addProperty(Edge.Property) - Method in class edu.cmu.tetrad.graph.Edge
addProperty.
addProperty(Edge.Property) - Method in class edu.cmu.tetrad.graph.EdgeTypeProbability
addProperty.
addPropertyChangeListener(PropertyChangeListener) - Method in class edu.cmu.tetrad.data.ContinuousVariable
Adds a property change listener.
addPropertyChangeListener(PropertyChangeListener) - Method in class edu.cmu.tetrad.data.DiscreteVariable
Adds a property change listener.
addPropertyChangeListener(PropertyChangeListener) - Method in class edu.cmu.tetrad.graph.Dag
Adds a PropertyChangeListener to the underlying graph object.
addPropertyChangeListener(PropertyChangeListener) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Adds a PropertyChangeListener to the graph.
addPropertyChangeListener(PropertyChangeListener) - Method in interface edu.cmu.tetrad.graph.Graph
Adds a PropertyChangeListener to the graph.
addPropertyChangeListener(PropertyChangeListener) - Method in class edu.cmu.tetrad.graph.GraphNode
Adds a property change listener.
addPropertyChangeListener(PropertyChangeListener) - Method in class edu.cmu.tetrad.graph.LagGraph
Adds a PropertyChangeListener to the graph.
addPropertyChangeListener(PropertyChangeListener) - Method in interface edu.cmu.tetrad.graph.Node
Adds a property change listener.
addPropertyChangeListener(PropertyChangeListener) - Method in class edu.cmu.tetrad.graph.SemGraph
Adds a PropertyChangeListener to the graph.
addPropertyChangeListener(PropertyChangeListener) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds a PropertyChangeListener to the list of listeners that are notified when a bound property is changed.
addPropertyChangeListener(PropertyChangeListener) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Registers a listener to events concerning the lag graph.
addRecord(Node, SortedSet<Node>, SortedSet<Node>, SortedSet<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch.LatentStructure
addRecord.
addRemove(Edge) - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Add another remove operation to the GraphChange.
addRow(List<? extends V>) - Method in interface edu.pitt.isp.sverchkov.data.DataTable
addRow.
addRow(List<? extends V>) - Method in class edu.pitt.isp.sverchkov.data.DataTableImpl
addRow.
addSimilarEdges(Node, Node) - Method in class edu.cmu.tetrad.search.SvarFges
Adds similar edges between two nodes.
addTetradLoggerConfig(Class<?>, TetradLoggerConfig) - Method in class edu.cmu.tetrad.util.TetradLogger
Adds the given TetradLoggerConfig to the logger, so that it can be used throughout the life of the application.
addTetradLoggerListener(TetradLoggerListener) - Method in class edu.cmu.tetrad.util.TetradLogger
Adds a TetradLoggerListener to the TetradLogger.
addToCluster(int, String) - Method in class edu.cmu.tetrad.data.Clusters
Adds the given variable to the given index.
addToTier(int, String) - Method in class edu.cmu.tetrad.data.Knowledge
Adds the given variable or wildcard cpdag to the given tier.
addToTiersByVarNames(List<String>) - Method in class edu.cmu.tetrad.data.Knowledge
Puts a variable into tier i if its name is xxx:ti for some xxx and some i.
addTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.search.utils.AlmostCycleRemover
Adds a triple consisting of three given nodes to the data structure.
addTwoCycles(Graph, int) - Static method in class edu.cmu.tetrad.graph.RandomGraph
addTwoCycles.
addUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Adds an underline triple to the current object.
addUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
addUnderlineTriple.
addUnderlineTriple(Node, Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
addUnderlineTriple.
addUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
addUnderlineTriple.
addUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
addUnderlineTriple.
addUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds an underline triple consisting of three nodes to the graph.
addUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Underlines
addUnderlineTriple.
addUndirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Adds an undirected edge between two nodes.
addUndirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Adds an undirected edge --- to the graph.
addUndirectedEdge(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Adds an undirected edge --- to the graph.
addUndirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Adds an undirected edge --- to the graph.
addUndirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Adds an undirected edge --- to the graph.
addUndirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Adds an undirected edge between two nodes.
addVariable(int, Node) - Method in class edu.cmu.tetrad.data.BoxDataSet
Adds the given variable at the given index.
addVariable(int, Node) - Method in interface edu.cmu.tetrad.data.DataSet
Adds the given variable at the given index.
addVariable(int, Node) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Adds the given variable at the given index.
addVariable(Node) - Method in class edu.cmu.tetrad.data.BoxDataSet
Adds the given variable to the data set.
addVariable(Node) - Method in interface edu.cmu.tetrad.data.DataSet
Adds the given variable to the data set.
addVariable(Node) - Method in class edu.cmu.tetrad.data.MixedDataBox
addVariable.
addVariable(Node) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Adds the given variable to the data set.
addVariable(String) - Method in class edu.cmu.tetrad.data.Knowledge
addVariable.
addVariable(String) - Method in class edu.cmu.tetrad.graph.LagGraph
addVariable.
adInd() - Method in record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Returns the value of the adInd record component.
AdjacencyConfusion - Class in edu.cmu.tetrad.algcomparison.statistic.utils
A confusion matrix for adjacencies--i.e.
AdjacencyConfusion(Graph, Graph) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.utils.AdjacencyConfusion
Constructs a new AdjacencyConfusion object from the given graphs.
AdjacencyFn - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
AdjacencyFn() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFn
Constructs the statistic.
AdjacencyFp - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
AdjacencyFp() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFp
Constructs the statistic.
AdjacencyFpr - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency true positive rate.
AdjacencyFpr() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFpr
Constructs the statistic.
AdjacencyPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
AdjacencyPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AdjacencyPrecision
Constructs the statistic.
AdjacencyRecall - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency recall.
AdjacencyRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AdjacencyRecall
Constructs the statistic.
AdjacencyTn - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
AdjacencyTn() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTn
Constructs the statistic.
AdjacencyTp - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
AdjacencyTp() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTp
Constructs the statistic.
AdjacencyTpr - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency true positive rate.
AdjacencyTpr() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTpr
Constructs the statistic.
adjacent(Node, Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns True iff a is adjacent to b in the current graph.
AdjCor - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The number of adjacency correct edges.
AdjCor - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant AdjCor
AdjFn - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The number of adjacency false negative edges.
AdjFn - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant AdjFn
AdjFp - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The number of adjacency false positive edges.
AdjFp - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant AdjFp
adjMatFromMGM() - Method in class edu.pitt.csb.mgm.Mgm
Converts MGM to matrix of doubles.
AdjPrec - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The adjacency precision.
AdjPrec - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant AdjPrec
AdjRec - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The adjacency recall.
AdjRec - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant AdjRec
adjustmentSets(Node, Node, int, int, int, int) - Method in class edu.cmu.tetrad.graph.Paths
An adjustment set for a pair of nodes <source, target> for a CPDAG is a set of nodes that blocks all paths from the source to the target that cannot contribute to a calculation for the total effect of the source on the target in any DAG in a CPDAG while not blocking any path from the source to the target that could be causal.
AdTree - Class in edu.cmu.tetrad.search.utils
An AD tree is a data structure used to store the data for a given dataset in a way that makes it easy to calculate cell counts for a multidimensional contingency table for a given set of variables.
AdTree<A,V> - Class in edu.pitt.isp.sverchkov.data
An implementation of a static AD tree based on Moore and Lee 1998 (mostly)
AdTree(DataSet) - Constructor for class edu.cmu.tetrad.search.utils.AdTree
Constructs an AD Leaf Tree for the given dataset, without subsampling.
AdTree(DataSet, List<Integer>) - Constructor for class edu.cmu.tetrad.search.utils.AdTree
Constructs an AD Leaf Tree for the given dataset.
AdTree(DataTable<A, V>) - Constructor for class edu.pitt.isp.sverchkov.data.AdTree
Constructs an AD tree for the given data set.
AdTreeTest - Class in edu.pitt.isp.sverchkov.data
A test of the AD tree implementation.
AdTreeTest() - Constructor for class edu.pitt.isp.sverchkov.data.AdTreeTest
Creates a new AdTreeTest object.
AhdCor - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The number of arrowhead false positive edges.
AhdCor - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant AhdCor
AhdFn - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The number of arrowhead false negative edges.
AhdFn - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant AhdFn
AhdFp - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The number of arrowhead false positive edges.
AhdFp - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant AhdFp
AhdPrec - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The arrowhead precision.
AhdPrec - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant AhdPrec
AhdRec - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The arrowhead recall.
AhdRec - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant AhdRec
Algorithm - Interface in edu.cmu.tetrad.algcomparison.algorithm
Interface that algorithm must implement.
Algorithm - Annotation Interface in edu.cmu.tetrad.annotation
Sep 5, 2017 10:47:30 AM
AlgorithmAnnotations - Class in edu.cmu.tetrad.annotation
Annotations for algorithms.
AlgorithmDescriptions - Class in edu.cmu.tetrad.util
Algorithm descriptions.
AlgorithmFactory - Class in edu.cmu.tetrad.algcomparison.algorithm
Aug 30, 2017 3:14:40 PM
Algorithms - Class in edu.cmu.tetrad.algcomparison.algorithm
A list of algorithm to be compared.
Algorithms() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.Algorithms
Constructs an empty list of algorithms.
algoType() - Element in annotation interface edu.cmu.tetrad.annotation.Algorithm
Description of the algorithm.
AlgType - Enum Class in edu.cmu.tetrad.annotation
Author : Jeremy Espino MD Created 6/30/17 10:36 AM
All - Enum constant in enum class edu.cmu.tetrad.data.DataType
All.
allDirectedPaths(Node, Node, int) - Method in class edu.cmu.tetrad.graph.Paths
Finds all directed paths from node1 to node2 with a maximum length.
allEdgeStats(Graph, Graph) - Static method in class edu.pitt.csb.mgm.MixedUtils
allEdgeStats.
allEdgeStats(Graph, Graph, HashMap<String, String>) - Static method in class edu.pitt.csb.mgm.MixedUtils
allEdgeStats.
allEigenvaluesAreSmallerThanOneInModulus(Matrix) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
allEigenvaluesAreSmallerThanOneInModulus.
allNodePairs(List<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Generates NodePairs of all possible pairs of nodes from given list of nodes.
ALLOW_INTERNAL_RANDOMNESS - Static variable in class edu.cmu.tetrad.util.Params
Constant ALLOW_INTERNAL_RANDOMNESS="allowInternalRandomness"
allow_latent_common_causes - Enum constant in enum class edu.cmu.tetrad.annotation.AlgType
If an algorithm allows latent common causes.
allPaths(Node, Node, int) - Method in class edu.cmu.tetrad.graph.Paths
Finds all paths from node1 to node2 within a specified maximum length.
allPaths(Node, Node, int, int, Set<Node>, Map<Node, Set<Node>>, boolean) - Method in class edu.cmu.tetrad.graph.Paths
Finds all paths between two nodes satisfying certain conditions.
allPaths(Node, Node, int, Set<Node>, boolean) - Method in class edu.cmu.tetrad.graph.Paths
Finds all paths between two nodes within a given maximum length, considering optional condition set and selection bias.
allPathsOutOf(Node, int, Set<Node>, boolean) - Method in class edu.cmu.tetrad.graph.Paths
Generates all paths out of a given node within a specified maximum length and conditional set.
AllSubsetsIndependenceFacts(Set<IndependenceFact>, Set<IndependenceFact>) - Constructor for class edu.cmu.tetrad.search.MarkovCheck.AllSubsetsIndependenceFacts
Constructor.
allToString() - Method in class edu.cmu.tetrad.simulation.PRAOerrors
allToString.
AlmostCycleRemover - Class in edu.cmu.tetrad.search.utils
A class for heuristically removing almost cycles from a PAG to avoid unfaithfulness in an estimated PAG.
AlmostCycleRemover() - Constructor for class edu.cmu.tetrad.search.utils.AlmostCycleRemover
Constructs a new instance of the AlmostCycleRemover class with the specified Graph.
alongPathIn(Graph) - Method in class edu.cmu.tetrad.graph.Triple
alongPathIn.
ALPHA - Static variable in interface edu.cmu.tetrad.graph.Node
Constant ALPHA
ALPHA - Static variable in class edu.cmu.tetrad.util.Params
Constant ALPHA="alpha"
ALPHA_NUM - Static variable in interface edu.cmu.tetrad.graph.Node
Constant ALPHA_NUM
AMBIGUOUS - Enum constant in enum class edu.cmu.tetrad.search.utils.GraphSearchUtils.CpcTripleType
An ambiguous triple.
AMBIGUOUS - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.VcPc.CpcTripleType
The triple is ambiguous.
AMBIGUOUS - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.VcPcFast.CpcTripleType
Constant AMBIGUOUS
amenablePathsMpdagMag(Node, Node, int) - Method in class edu.cmu.tetrad.graph.Paths
Finds amenable paths from the given source node to the given destination node with a maximum length.
amenablePathsPag(Node, Node, int) - Method in class edu.cmu.tetrad.graph.Paths
Finds amenable paths from the given source node to the given destination node with a maximum length, for a PAG.
AncestorF1 - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the F1 statistic for adjacencies.
AncestorF1() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AncestorF1
Constructs the statistic.
AncestorPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
Ancestor precision.
AncestorPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AncestorPrecision
Constructs the statistic.
AncestorRecall - Class in edu.cmu.tetrad.algcomparison.statistic
Ancestor recall.
AncestorRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AncestorRecall
Constructs the statistic.
AncestralPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
AncestralPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AncestralPrecision
Constructs the statistic.
AncestralRecall - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
AncestralRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AncestralRecall
Constructs the statistic.
andersonDarling - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Score
The Anderson-Darling score.
AndersonDarlingTest - Class in edu.cmu.tetrad.data
Implements the Anderson-Darling test for normality, with P values calculated as in R's ad.test method (in package nortest).
AndersonDarlingTest(double[]) - Constructor for class edu.cmu.tetrad.data.AndersonDarlingTest
Constructs an Anderson-Darling test for the given column of data.
AnnotatedClass<T> - Class in edu.cmu.tetrad.annotation
Represents a class that encapsulates a class along with its associated annotation.
AnnotatedClass(Class<?>, T) - Constructor for class edu.cmu.tetrad.annotation.AnnotatedClass
Creates an annotated class.
AnnotatedClassUtils - Class in edu.cmu.tetrad.annotation
Sep 6, 2017 11:11:38 AM
annotation() - Method in class edu.cmu.tetrad.annotation.AnnotatedClass
Gets the annotation.
anteriority(Graph, Node...) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Computes the anteriority of the given nodes in a graph.
anteriority(Node...) - Method in class edu.cmu.tetrad.graph.Paths
Returns the set of nodes that are in the anteriority of the given nodes in the graph.
ANY_DAG - Static variable in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Any DAG uniformly selected
append(int[], int) - Method in interface edu.cmu.tetrad.search.score.Score
Appends an extra int to a list of ints.
APPLY_R1 - Static variable in class edu.cmu.tetrad.util.Params
Constant APPLY_R1="applyR1"
applyDmSearch(Graph, Set<String>, double) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
applyDmSearch.
applyTo(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Outputs a new PAG, a copy of the input excepting the applied changes of this object.
ApproximateUpdater - Class in edu.cmu.tetrad.bayes
Calculates updated marginals for a Bayes net by simulating data and calculating likelihood ratios.
ApproximateUpdater(BayesIm) - Constructor for class edu.cmu.tetrad.bayes.ApproximateUpdater
Constructs a new updater for the given Bayes net.
ApproximateUpdater(BayesIm, Evidence) - Constructor for class edu.cmu.tetrad.bayes.ApproximateUpdater
Constructs a new updater for the given Bayes net.
ar(DataSet, int) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
ar.
ar2(DataSet, int) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
ar2.
archiveCurrentDirectory() - Method in class edu.cmu.tetrad.util.TetradSerializableUtils
Creates a zip archive of the currently serialized files in getCurrentDirectory(), placing the archive in getArchiveDirectory().
arrangeByKnowledgeTiers(Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
arrangeByKnowledgeTiers.
arrangeByKnowledgeTiers(Graph, Knowledge) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
arrangeByKnowledgeTiers.
arrangeByLayout(Graph, HashMap<String, PointXy>) - Static method in class edu.cmu.tetrad.graph.LayoutUtil
arrangeByLayout.
arrangeBySourceGraph(Graph, Graph) - Static method in class edu.cmu.tetrad.graph.LayoutUtil
Arranges the nodes in the result graph according to their positions in the source graph.
arrayPermute(double[]) - Static method in class edu.pitt.csb.mgm.MixedUtils
arrayPermute.
arrayPermute(int[]) - Static method in class edu.pitt.csb.mgm.MixedUtils
arrayPermute.
ARROW - Enum constant in enum class edu.cmu.tetrad.graph.Endpoint
Arrow endpoint.
ArrowConfusion - Class in edu.cmu.tetrad.algcomparison.statistic.utils
A confusion matrix for arrows--i.e.
ArrowConfusion(Graph, Graph) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
Constructs a new ArrowConfusion object.
ArrowConfusion(Graph, Graph, boolean) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
Constructs a new ArrowConfusion object.
ArrowheadFn - Class in edu.cmu.tetrad.algcomparison.statistic
The arrow precision.
ArrowheadFn() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFn
Constructs the statistic.
ArrowheadFp - Class in edu.cmu.tetrad.algcomparison.statistic
The arrow precision.
ArrowheadFp() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFp
Constructs the statistic.
ArrowheadFpr - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency true positive rate.
ArrowheadFpr() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFpr
Constructs the statistic.
ArrowheadPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The arrow precision.
ArrowheadPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecision
Constructs the statistic.
ArrowheadPrecisionCommonEdges - Class in edu.cmu.tetrad.algcomparison.statistic
The arrow precision.
ArrowheadPrecisionCommonEdges() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecisionCommonEdges
Constructs the statistic.
ArrowheadRecall - Class in edu.cmu.tetrad.algcomparison.statistic
The arrow recall.
ArrowheadRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecall
Constructs the statistic.
ArrowheadRecallCommonEdges - Class in edu.cmu.tetrad.algcomparison.statistic
The arrow recall.
ArrowheadRecallCommonEdges() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecallCommonEdges
Constructs the statistic.
ArrowheadTn - Class in edu.cmu.tetrad.algcomparison.statistic
The arrow precision.
ArrowheadTn() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTn
Constructs the statistic.
ArrowheadTp - Class in edu.cmu.tetrad.algcomparison.statistic
The arrow precision.
ArrowheadTp() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTp
Constructs the statistic.
ASCENDING - Static variable in class edu.cmu.tetrad.util.RocCalculator
Constant ASCENDING=0
asList(int[]) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Creates a new list containing the elements of the given array.
asList(int[], List<Node>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Constructs a list of nodes from the given nodes list at the given indices in that list.
asRow(double[]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
asRow.
asSet(int[], List<Node>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts an array of indices into a set of corresponding nodes from a given list of nodes.
asSet(Node...) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts the given array of nodes into a Set of nodes.
assign(double) - Method in class edu.cmu.tetrad.util.Vector
assign.
assign(Matrix) - Method in class edu.cmu.tetrad.util.Matrix
assign.
assign(Vector) - Method in class edu.cmu.tetrad.util.Vector
assign.
assignColumn(int, Vector) - Method in class edu.cmu.tetrad.util.Matrix
assignColumn.
assignRow(int, Vector) - Method in class edu.cmu.tetrad.bayes.CptMapProbs
Assigns the values in the provided vector to a specific row in the probability map.
assignRow(int, Vector) - Method in class edu.cmu.tetrad.util.Matrix
assignRow.
at - Enum constant in enum class edu.cmu.tetrad.graph.EdgeTypeProbability.EdgeType
Arrow-to-tail
average - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Wilkinson's method
average - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
`The average method.
AverageDegreeEst - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
AverageDegreeEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeEst
Constructs the statistic.
AverageDegreeTrue - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
AverageDegreeTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeTrue
Constructs the statistic.
averageDeviation(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
averageDeviation.
averageDeviation(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
averageDeviation.
averageDeviation(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
averageDeviation.
averageDeviation(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
averageDeviation.
averagetest - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Average method
averagetest - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
The average test method.
AVG_DEGREE - Static variable in class edu.cmu.tetrad.util.Params
Constant AVG_DEGREE="avgDegree"

B

b() - Method in record class edu.cmu.tetrad.search.score.SemBicScore.CovAndCoefs
Returns the value of the b record component.
BasalInitializer - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Initializes a history array by setting the value of each variable to basal if it is unregulated (has no parents other than itself one time step back) and to a random value chosen from a N(basal, initStDev) distribution otherwise.
BasalInitializer(UpdateFunction, double, double) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasalInitializer
Constructs a new history that will initialize genes using the given basal expression and initial standard deviation.
basicCpdag(Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Get a graph and direct only the unshielded colliders.
basicCpdagRestricted2(Graph, Node) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
basicCpdagRestricted2.
BasicGraph - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util
Basic functionality that all graph-derived classes should provide.
BasicGraph(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Creates a Graph reading it from file fname.
BasicGraph(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Creates a graph with gName name, and n nodes.
BasicLagGraph - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Stores a time series in the "update" (rather than, say, the "repeated") form--that is, for a given set of factors (the word "factor" is being used here to avoid ambiguity), only lags behind the getModel time step are recorded temporally, with causal edges extending from lagged factors with lags >= 1 to factors in the getModel time step (lag = 0) only.
BasicLagGraph() - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Constructs an empty update graph--that is, a graph with no factors (and therefore no edges).
BasicLagGraph(LagGraph) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Constructs a copy of the given lag graph.
BasicLTMatrix - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util
Implements a space-efficient Lower Triangular Matrix of elements of type short
BasicLTMatrix(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicLTMatrix
Creates a lower triangular matrix reading it from file fname.
BasicLTMatrix(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicLTMatrix
Creates a lower triangular matrix with nrows rows.
BasicMatrix - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util
Basic functionality of a Matrix
BasicMatrix(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Creates a matrix reading it from a file fname.
BasicMatrix(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Creates a matrix with nrows rows, and with name mname.
BASIS_SCALE - Static variable in class edu.cmu.tetrad.util.Params
Constant BASIS_TYPE="basisType"
BASIS_TYPE - Static variable in class edu.cmu.tetrad.util.Params
Constant BASIS_TYPE="basisType"
BasisFunctionBicScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for Basis Function BIC Score (Basis-BIC).
BasisFunctionBicScore - Class in edu.cmu.tetrad.search.score
Calculates the basis function BIC score for a given dataset.
BasisFunctionBicScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.BasisFunctionBicScore
Initializes a new instance of the BasisFunctionBicScore class.
BasisFunctionBicScore(DataSet, boolean, int, int, double) - Constructor for class edu.cmu.tetrad.search.score.BasisFunctionBicScore
Constructs a BasisFunctionBicScore object with the specified parameters.
BasisFunctionBicTest - Class in edu.cmu.tetrad.algcomparison.independence
 
BasisFunctionBicTest() - Constructor for class edu.cmu.tetrad.algcomparison.independence.BasisFunctionBicTest
Constructs a new instance of the Basis Function BIC test.
basisFunctionValue(int, int, double) - Static method in class edu.cmu.tetrad.util.StatUtils
Performs a calculation that involves repeatedly multiplying an initial value of `1.0` by the product of `0.95` and a given parameter `x`, iterating `index` times.
BayesBifParser - Class in edu.cmu.tetrad.bayes
The BayesBifParser class provides a set of static methods for parsing Bayesian Network Interchange Format (BIF) files.
BayesBifRenderer - Class in edu.cmu.tetrad.bayes
Renders Bayes nets and related models in XML.
BayesianConstraintInference - Class in edu.pitt.dbmi.algo.bayesian.constraint.inference
Feb 22, 2014 3:26:17 PM
BayesianConstraintInference() - Constructor for class edu.pitt.dbmi.algo.bayesian.constraint.inference.BayesianConstraintInference
Constructor.
BayesianConstraintInferenceTest - Class in edu.pitt.dbmi.algo.bayesian.constraint.inference
Feb 22, 2014 3:35:38 PM
BayesianConstraintInferenceTest() - Constructor for class edu.pitt.dbmi.algo.bayesian.constraint.inference.BayesianConstraintInferenceTest
Constructor.
BayesIm - Interface in edu.cmu.tetrad.bayes
Interface implemented by Bayes instantiated models.
BayesImParser - Class in edu.cmu.tetrad.search.utils
Takes an xml element representing a bayes im and converts it to a BayesIM
BayesImParser() - Constructor for class edu.cmu.tetrad.search.utils.BayesImParser
Creates a new BayesImParser.
BayesImProbs - Class in edu.cmu.tetrad.bayes
Calculates cell probabilities from conditional BayesIm probabilities on the fly without constructing the entire table.
BayesImProbs(BayesIm) - Constructor for class edu.cmu.tetrad.bayes.BayesImProbs
Constructs a BayesImProbs object from the given BayesIm.
BayesNetSimulation - Class in edu.cmu.tetrad.algcomparison.simulation
Bayes net simulation.
BayesNetSimulation(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Constructs a new BayesNetSimulation.
BayesNetSimulation(BayesIm) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Constructs a new BayesNetSimulation.
BayesNetSimulation(BayesPm) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Constructs a new BayesNetSimulation.
BayesPm - Class in edu.cmu.tetrad.bayes
Implements a discrete Bayes parametric model--that is, a DAG together with a map from the nodes in the graph to a set of discrete variables, specifying the number of categories for each variable and the name of each category for each variable.
BayesPm(BayesPm) - Constructor for class edu.cmu.tetrad.bayes.BayesPm
Copy constructor.
BayesPm(Graph) - Constructor for class edu.cmu.tetrad.bayes.BayesPm
Construct a new BayesPm using the given DAG, assigning each variable two values named "value1" and "value2" unless nodes are discrete variables with categories already defined.
BayesPm(Graph, int, int) - Constructor for class edu.cmu.tetrad.bayes.BayesPm
Constructs a new BayesPm from the given DAG, assigning each variable a random number of values between lowerBound and upperBound.
BayesPm(Graph, BayesPm) - Constructor for class edu.cmu.tetrad.bayes.BayesPm
Constructs a new BayesPm using a given DAG, using as much information from the old BayesPm as possible.
BayesPm(Graph, BayesPm, int, int) - Constructor for class edu.cmu.tetrad.bayes.BayesPm
Constructs a new BayesPm from the given DAG, using as much information from the old BayesPm as possible.
BayesProperties - Class in edu.cmu.tetrad.bayes
Calculates some scores for Bayes nets as a whole.
BayesProperties(DataSet) - Constructor for class edu.cmu.tetrad.bayes.BayesProperties
Constructs a new BayesProperties object for the given data set.
BayesProperties.LikelihoodRet - Class in edu.cmu.tetrad.bayes
The LikelihoodRet class represents the result of a likelihood ratio test.
BayesUpdater - Interface in edu.cmu.tetrad.bayes
Interface for a discrete Bayes updating algorithm.
BayesXmlParser - Class in edu.cmu.tetrad.bayes
Parses Bayes elements back to objects.
BayesXmlParser() - Constructor for class edu.cmu.tetrad.bayes.BayesXmlParser
A parser for Bayes XML files.
BayesXmlRenderer - Class in edu.cmu.tetrad.bayes
Renders Bayes nets and related models in XML.
BAYS_NET - Static variable in class edu.cmu.tetrad.algcomparison.simulation.SimulationTypes
Constant BAYS_NET="Bayes Net (Multinomial)"
BCCausalInference - Class in edu.pitt.dbmi.algo.bayesian.constraint.inference
This is a thread-safe version of BCInference.
BCCausalInference(int[], int[][]) - Constructor for class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCCausalInference
Constructor
BCCausalInference.OP - Enum Class in edu.pitt.dbmi.algo.bayesian.constraint.inference
An enum for the type of operation.
BCInference - Class in edu.pitt.dbmi.algo.bayesian.constraint.inference
Feb 26, 2014 8:07:20 PM
BCInference(int[][], int[]) - Constructor for class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCInference
Cases is a two-dimensional array dataset.
BCInference.OP - Enum Class in edu.pitt.dbmi.algo.bayesian.constraint.inference
Enum for the type of constraint.
BdeMetricCache - Class in edu.cmu.tetrad.bayes
Provides a method for computing the score of a model, called the BDe metric (Bayesian Dirchlet likelihood equivalence), given a dataset (assumes no missing values) and a Bayes parameterized network (assumes no latent variables).> 0
BdeMetricCache(DataSet, BayesPm) - Constructor for class edu.cmu.tetrad.bayes.BdeMetricCache
Constructs a BdeMetricCache object for a given dataset and BayesPm.
BdeScore - Class in edu.cmu.tetrad.search.score
Calculates the BDe score (Bayes Dirichlet Equivalent) score for analyzing discrete multinomial data.
BdeScore(DataSet) - Constructor for class edu.cmu.tetrad.search.score.BdeScore
Constructs a BDe score for the given dataset.
BDeu - Enum constant in enum class edu.cmu.tetrad.sem.ScoreType
the BDeu score
BdeuScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for Fisher Z test.
BdeuScore - Class in edu.cmu.tetrad.search.score
Calculates the BDeu score, which the BDe (Bayes Dirichlet Equivalent) score with uniform priors.
BdeuScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.BdeuScore
Constructs a new instance of the test.
BdeuScore(DataSet) - Constructor for class edu.cmu.tetrad.search.score.BdeuScore
Constructs a BDe score for the given dataset.
BdeuTest - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Fisher Z test.
BdeuTest() - Constructor for class edu.cmu.tetrad.algcomparison.independence.BdeuTest
Constructs a new instance of the test.
bernoulliRand(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
bernoulliRand.
bes(Graph, List<Node>) - Method in class edu.cmu.tetrad.search.utils.Bes
Runs BES for a graph over the given list of variables
bes(Graph, List<Node>, List<Node>) - Method in class edu.cmu.tetrad.search.utils.BesPermutation
Runs BES.
Bes - Class in edu.cmu.tetrad.search.utils
Extracts the backward step of GES for use GES but also in other algorithms.
Bes(Score) - Constructor for class edu.cmu.tetrad.search.utils.Bes
Constructs the search.
Bes.Arrow - Class in edu.cmu.tetrad.search.utils
An arrow in the search.
BesPermutation - Class in edu.cmu.tetrad.search.utils
Implements a version of the BES (Best Equivalent Search) algorithm that takes a permutation as input and yields a permtuation as output, where the related DAG or CPDAG models are implied by the ordering or variables in these permutations.
BesPermutation(Score) - Constructor for class edu.cmu.tetrad.search.utils.BesPermutation
Constructor.
bestOrder(List<Node>) - Method in class edu.cmu.tetrad.search.Grasp
Given an initial permutation, 'order,' of the variables, searches for a best permutation of the variables by rearranging the variables in 'order.'
bestOrder(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
bestOrder.
beta(double, double) - Static method in class edu.cmu.tetrad.util.StatUtils
Calculates the value of beta for doubles
Beta - Class in edu.cmu.tetrad.util.dist
Implements a Beta distribution for purposes of drawing random numbers.
betaCdf(double, double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
Incomplete Beta function.
betaPdf(double, double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
betaPdf.
betaQuantile(double, double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
betaQuantile.
betaRand(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
Beta distribution random generator.
betterMutation(TeyssierScorer) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
betterMutation.
Bfci - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
Adjusts GFCI to use a permutation algorithm (such as BOSS-Tuck) to do the initial steps of finding adjacencies and unshielded colliders.
Bfci() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
No-arg constructor.
Bfci(IndependenceWrapper, ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Constructs a new BFCI algorithm using the given test and score.
BFci - Class in edu.cmu.tetrad.search
Uses BOSS in place of FGES for the initial step in the GFCI algorithm.
BFci(IndependenceTest, Score) - Constructor for class edu.cmu.tetrad.search.BFci
Constructor.
bfsAllPathsOutOfX(Graph, Set<Node>, Set<Node>, Set<Node>, int, Node, Node, boolean) - Static method in class edu.cmu.tetrad.search.SepsetFinder
Performs a breadth-first search to find all paths out of a specific node in a graph, considering certain conditions and constraints.
bic - Variable in class edu.cmu.tetrad.bayes.BayesProperties.LikelihoodRet
The BIC.
BIC - Enum constant in enum class edu.cmu.tetrad.search.score.GicScores.RuleType
The Bayesian Information Criterion.
BicDiff - Class in edu.cmu.tetrad.algcomparison.statistic
Difference between the true and estimated BIC scores.
BicDiff() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.BicDiff
Constructs a new instance of the statistic.
BicDiffPerRecord - Class in edu.cmu.tetrad.algcomparison.statistic
Difference between the true and estiamted BIC scores.
BicDiffPerRecord() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.BicDiffPerRecord
Constructs a new instance of the statistic.
BicEst - Class in edu.cmu.tetrad.algcomparison.statistic
Estimated BIC score.
BicEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.BicEst
No-arg constructor.
BicTrue - Class in edu.cmu.tetrad.algcomparison.statistic
True BIC score.
BicTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.BicTrue
Constructs a new instance of the statistic.
BidirectedConfusion - Class in edu.cmu.tetrad.algcomparison.statistic.utils
A confusion matrix for bidireced edges--i.e.
BidirectedConfusion(Graph, Graph) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.utils.BidirectedConfusion
Constructs a new confusion matrix for bidirected edges.
bidirectedEdge(Node, Node) - Static method in class edu.cmu.tetrad.graph.Edges
Constructs a new bidirected edge from nodeA to nodeB (<->).
BidirectedEst - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
BidirectedEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.BidirectedEst
Constructs a new instance of the statistic.
BidirectedFP - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected false negatives.
BidirectedFP() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.BidirectedFP
Constructs a new instance of the statistic.
BidirectedLatentPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The BidirectedLatentPrecision class implements the Statistic interface and represents a statistic that calculates the percentage of bidirected edges in an estimated graph for which a latent confounder exists in the true graph.
BidirectedLatentPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.BidirectedLatentPrecision
The BidirectedLatentPrecision class implements the Statistic interface and represents a statistic that calculates the percentage of bidirected edges in an estimated graph for which a latent confounder exists in the true graph.
BidirectedPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected edge precision.
BidirectedPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.BidirectedPrecision
Constructs a new instance of the statistic.
BidirectedRecall - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected edge precision.
BidirectedRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.BidirectedRecall
Constructs a new instance of the statistic.
bidirectedToUndirected(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts a bidirected graph to an undirected graph.
BidirectedTP - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
BidirectedTP() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.BidirectedTP
Constructs a new instance of the statistic.
BidirectedTrue - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
BidirectedTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.BidirectedTrue
Constructs a new instance of the statistic.
binDep() - Method in record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Returns the value of the binDep record component.
binIndep() - Method in record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Returns the value of the binIndep record component.
binomialCdf(int, int, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
Binomial cumulative distribution function.
binomialPmf(int, int, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
binomialPmf.
binomialQuantile(double, int, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
binomialQuantile.
binomialRand(int, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
Binomial random generator from Numerical Recipes
biNormalCdf(double, double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
Bivariate normal CDF.
Biolingua - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua
Implements an algorithm for revising regulatory models with expression data.
BiolinguaAlgorithm(SymMatrixF, BiolinguaDigraph) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Biolingua
Runs the biolingua algorithm using the given correlation matrix (all values are assumed significant) and the initial graph, and uses some default values for the coefficients in the evaluation metric for annotations, errors, links, and predictions.
BiolinguaAlgorithm(SymMatrixF, BiolinguaDigraph, float, float, float, float) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Biolingua
Runs the biolingua algorithm using the given correlation matrix (all values are assumed significant), an initial graph, and the coefficients in the evaluation metric for annotations, errors, links, and predictions.
BiolinguaAlgorithm(SymMatrixF, SymMatrixF, BiolinguaDigraph, float, float, float, float) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Biolingua
Runs the biolingua algorithm using the given correlation matrix, significance matrix, the initial graph, and the coefficients in the evaluation metric for annotations, errors, links, and predictions.
BiolinguaDigraph - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua
Implements a digraph to be used by the Biolingua algorithm.
BiolinguaDigraph(BiolinguaDigraph) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.BiolinguaDigraph
Copy constructor.
BiolinguaDigraph(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.BiolinguaDigraph
Creates a BiolinguaDigraph reading it from file fname.
BiolinguaDigraph(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.BiolinguaDigraph
Creates a BiolinguaDigraph with name gName and n nodes
BiolinguaRunner - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua
Client of the Biolingua class, can be used to easily run the algorithm with different inputs.
BiolinguaRunner() - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.BiolinguaRunner
Initializes a new instance of the BiolinguaRunner class.
blankDirichletIm(BayesPm) - Static method in class edu.cmu.tetrad.bayes.DirichletBayesIm
blankDirichletIm.
blockPathsLocalMarkov(Graph, Node) - Static method in class edu.cmu.tetrad.search.SepsetFinder
Returns a set of nodes that are the parents of the given node in the graph.
blockPathsNoncollidersOnly(Graph, Node, Node, int, boolean) - Static method in class edu.cmu.tetrad.search.SepsetFinder
Returns a set that blocks all paths that can be blocked by conditioning on noncolliders only, searching outward from x.
blockPathsRecursively(Graph, Node, Node, Set<Node>, Set<Node>, int) - Static method in class edu.cmu.tetrad.search.SepsetFinder
Retrieves set that blocks all blockable paths between x and y in the given graph, where this set contains the given nodes.
blockPathsWithMarkovBlanket(Node, Graph) - Static method in class edu.cmu.tetrad.search.SepsetFinder
Identifies the set of nodes that form the Markov Blanket for a given node in a graph.
bookmark() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Bookmarks the current pi with index Integer.MIN_VALUE.
bookmark(int) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Bookmarks the current pi as the index key.
bool2(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.BoolSearch
Implements the BOOL-2 algorithm of Akutsu, et al, found in section 2.2 of their paper "Algorithms for Inferring Qualitative Models of Biological Networks".
bool2(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.BoolSearch
Implements the BOOL-2 algorithm of Akutsu, et al, found in section 2.2 of their paper "Algorithms for Inferring Qualitative Models of Biological Networks".
BOOLEAN_GLASS_SIMULATION - Static variable in class edu.cmu.tetrad.algcomparison.simulation.SimulationTypes
Constant BOOLEAN_GLASS_SIMULATION="Boolean Glass Simulation"
BooleanFunction - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Stores a boolean function from a set of boolean-valued parents to a single boolean-valued column.
BooleanFunction(IndexedParent[]) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
Constructs a new boolean function for the given array of parents.
BooleanGlassFunction - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Updates a gene given a history using the formula Gi.0 = max(Gi.1 - decayRate * -Gi.1 + booleanInfluenceRate * F(Parents(Gi) in the graph \ Gi.1), lowerBound), as described in Edwards and Glass, (2000), "Combinatorial explosion in model gene networks", American Institute of Physics.
BooleanGlassFunction(LagGraph) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Constructs a new random boolean Glass function using the given lag graph, with a basalExpression of 0.0, a true value of +1.0 and a false value of -1.0.
BooleanGlassFunction(LagGraph, double, double) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Constructs a new random boolean Glass function using the given lag graph, lower bound, and basalExpression.
booleanRepresentation(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.BoolSearch
Computes a byte vector which corresponds to the argument ind.
booleanRepresentation(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch
Computes a byte vector which corresponds to the argument ind.
booleanRepresentation(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealEvaluator
Computes a byte vector which corresponds to the argument ind.
booleanRepresentation(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.BoolSearch
Computes a byte vector which corresponds to the argument ind.
booleanRepresentation(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.LTestReveal
Computes a byte vector which corresponds to the argument ind.
booleanRepresentation(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealEvaluator
Computes a byte vector which corresponds to the argument ind.
BoolSearch - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu
This class contains as a member variable (cases) the time series data stored in an int array of microarray measurements.
BoolSearch - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
This class contains as a member variable (cases) the time series data stored in an int array of microarray measurements.
BoolSearch(int[][], String[]) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.BoolSearch
Constructor
BoolSearch(int[][], String[]) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.BoolSearch
Constructor for BoolSearch.
BOOTSTRAP - Enum constant in enum class edu.cmu.tetrad.search.Cstar.SampleStyle
Use bootstrap.
Bootstrapping - Annotation Interface in edu.cmu.tetrad.annotation
Indicate algorithm can do bootstrapping.
BOOTSTRAPPING_NUM_THREADS - Static variable in class edu.cmu.tetrad.util.Params
Constant BOOTSTRAPPING_NUM_THEADS="bootstrappingNumThreads"
BootstrapSampler - Class in edu.cmu.tetrad.data
Provides a static method for sampling with replacement from a dataset to create a new dataset with a sample size supplied by the user.
BootstrapSampler() - Constructor for class edu.cmu.tetrad.data.BootstrapSampler
Constructs a sample that does not do any logging.
bootStrapSampling(DataSet, int) - Method in class edu.cmu.tetrad.calibration.DataForCalibrationRfci
bootStrapSampling.
Boss - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
BOSS (Best Order Score Search)
Boss - Class in edu.cmu.tetrad.search
Implements Best Order Score Search (BOSS).
Boss() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Boss
Constructs a new BOSS algorithm.
Boss(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Boss
Constructs a new BOSS algorithm with the given score.
Boss(Score) - Constructor for class edu.cmu.tetrad.search.Boss
This algorithm will work with an arbitrary BIC score.
BOSS - Enum constant in enum class edu.cmu.tetrad.search.Cstar.CpdagAlgorithm
The BOSS algorihtm.
BOSS - Enum constant in enum class edu.cmu.tetrad.search.FaskOrig.AdjacencyMethod
A permutation search with the BOSS algorithm.
BOSS - Enum constant in enum class edu.cmu.tetrad.search.LvLite.START_WITH
Start with BOSS.
BOSS_ALG - Static variable in class edu.cmu.tetrad.util.Params
Constant BOSS_ALG="bossAlg"
BossDumb - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
This class represents the LV-Lite algorithm, which is an implementation of the GFCI algorithm for learning causal structures from observational data using the BOSS algorithm as an initial CPDAG and using all score-based steps afterward.
BossDumb() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossDumb
This class represents a LV-Lite algorithm.
BossDumb(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossDumb
LV-Lite is a class that represents a LV-Lite algorithm.
BossLingam - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
BOSS-LiNGAM algorithm.
BossLingam - Class in edu.cmu.tetrad.search
Implements an algorithm which first finds a CPDAG for the variables and then uses a non-Gaussian orientation method to orient the undirected edges.
BossLingam() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossLingam
Constructs a new BOSS-LiNGAM algorithm.
BossLingam(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossLingam
Constructs a new BOSS-LiNGAM algorithm with the given score.
BossLingam(Graph, DataSet) - Constructor for class edu.cmu.tetrad.search.BossLingam
Constructor.
BossPag - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
This class represents the LV-Lite algorithm, which is an implementation of the GFCI algorithm for learning causal structures from observational data using the BOSS algorithm as an initial CPDAG and using all score-based steps afterward.
BossPag() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPag
This class represents a LV-Lite algorithm.
BossPag(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPag
LV-Lite is a class that represents a LV-Lite algorithm.
BOTH - Enum constant in enum class edu.cmu.tetrad.calculator.expression.ExpressionDescriptor.Position
The expression can occur in both the prefix and infix position.
BoxDataSet - Class in edu.cmu.tetrad.data
Wraps a DataBox in such a way that mixed data sets can be stored.
BoxDataSet(BoxDataSet) - Constructor for class edu.cmu.tetrad.data.BoxDataSet
Makes of copy of the given data set.
BoxDataSet(DataBox, List<Node>) - Constructor for class edu.cmu.tetrad.data.BoxDataSet
Constructs a new data set with the given number of rows and columns, with all values set to missing.
Bpc - Class in edu.cmu.tetrad.algcomparison.algorithm.cluster
Build Pure Clusters.
Bpc - Class in edu.cmu.tetrad.search
Implements the Build Pure Clusters (BPC) algorithm, which allows one to identify clusters of measured variables in a dataset that are explained by a single latent.
Bpc() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.cluster.Bpc
Constructs a new BPC algorithm.
Bpc(DataSet, double, BpcTestType) - Constructor for class edu.cmu.tetrad.search.Bpc
Constructor.
Bpc(ICovarianceMatrix, double, BpcTestType) - Constructor for class edu.cmu.tetrad.search.Bpc
Constructor.
BpcAlgorithmType - Enum Class in edu.cmu.tetrad.search.utils
Enumerates the algorithm types for BuildPureClusters, and Purify.
BpcTestType - Enum Class in edu.cmu.tetrad.search.utils
Enumerates the test types for BuildPureClusters, and Purify.
BpcTetradPurifyWashdown - Class in edu.cmu.tetrad.search.work_in_progress
Implements a really simple idea for building pure clusters, just using the Purify algorithm.
BpcTetradPurifyWashdown(DataSet, BpcTestType, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.BpcTetradPurifyWashdown
Construct the algorithm using a data set.
BpcTetradPurifyWashdown(ICovarianceMatrix, BpcTestType, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.BpcTetradPurifyWashdown
Construct the algorithm using a covariance matrix.
BryanSensitivityStudy - Class in edu.cmu.tetrad.study.examples.conditions
An example script to simulate data and run a comparison analysis on it.
BUILD_PURE_CLUSTERS - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcAlgorithmType
This one will work and does a good job for medium-sized models.
buildIndexing(List<Node>) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
buildIndexing.
buildTable(List<DiscreteVariable>) - Method in class edu.cmu.tetrad.search.utils.AdTree
Builds the contingency table based on the given list of discrete variables.
bumpInitialization(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.DishModel
Bumps the given expression value in the manner prescribed for the getModel dish.
ByteDataBox - Class in edu.cmu.tetrad.data
Stores a 2D array of byte data.
ByteDataBox(byte[][]) - Constructor for class edu.cmu.tetrad.data.ByteDataBox
Constructs a new data box using the given 2D byte data array as data.
ByteDataBox(int, int) - Constructor for class edu.cmu.tetrad.data.ByteDataBox
Constructs an 2D byte array consisting entirely of missing values (-99).

C

ca - Enum constant in enum class edu.cmu.tetrad.graph.EdgeTypeProbability.EdgeType
Circle-to-arrow
CACHE_SCORES - Static variable in class edu.cmu.tetrad.util.Params
Constant CACHE_SCORES="cacheScores"
calcAdjacencyGraph(Graph) - Static method in class edu.cmu.tetrad.search.utils.DagToPag
Calculates the adjacency graph for the given Directed Acyclic Graph (DAG).
calcChiSquare(int[], double) - Method in class edu.cmu.tetrad.search.test.ChiSquareTest
Calculates chi square for a conditional cross-tabulation table for independence question 0 _||_ 1 | 2, 3, ...max by summing up chi square and degrees of freedom for each conditional table in turn.
calcChiSquare(Sextad[]) - Method in class edu.cmu.tetrad.search.utils.DeltaSextadTest
Takes a list of tetrads for the given data set and returns the chi square value for the test.
calcChiSquare(Tetrad...) - Method in class edu.cmu.tetrad.search.utils.DeltaTetradTest
Takes a list of tetrads for the given data set and returns the chi square value for the test.
calcMargin(int[]) - Method in interface edu.cmu.tetrad.data.CellTable
Calculates the marginal sum for the cell table based on the given coordinates.
calcMargin(int[]) - Method in class edu.cmu.tetrad.data.CellTableAdTree
Calculates a marginal sum for the cell table.
calcMargin(int[]) - Method in class edu.cmu.tetrad.data.CellTableCountSample
Calculates a marginal sum for the cell table.
calcMargin(int[], int[]) - Method in interface edu.cmu.tetrad.data.CellTable
Calculates the marginal sum for the cell table based on the given coordinates and margin variables.
calcMargin(int[], int[]) - Method in class edu.cmu.tetrad.data.CellTableAdTree
An alternative way to specify a marginal calculation.
calcMargin(int[], int[]) - Method in class edu.cmu.tetrad.data.CellTableCountSample
An alternative way to specify a marginal calculation.
CALCULATE_FROM_SEM - Enum constant in enum class edu.cmu.tetrad.sem.StandardizedSemIm.Initialization
Calculate from SEM.
calculateCentralMoment(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
 
calculateCumulant(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
 
calculateMinimumTotalEffectsOnY(Node) - Method in class edu.cmu.tetrad.search.Ida
Returns a map from nodes in V \ {Y} to their minimum effects.
calculateMoment(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
 
calculatePriorMarginals(int) - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
Calculates the prior marginal probabilities of the given node.
calculatePriorMarginals(int) - Method in interface edu.cmu.tetrad.bayes.BayesUpdater
Calculates the prior marginal probabilities of the given node.
calculatePriorMarginals(int) - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
Calculates the prior marginal probabilities of the given node.
calculatePriorMarginals(int) - Method in class edu.cmu.tetrad.bayes.Identifiability
Calculates the prior marginal probabilities of the given node.
calculatePriorMarginals(int) - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Calculates the prior marginal probabilities of the given node.
calculatePriorMarginals(int) - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
Calculates the prior marginal probabilities of the given node.
calculateUpdatedMarginals(int) - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
Calculates the updated marginal probabilities of the given node, given the evidence.
calculateUpdatedMarginals(int) - Method in interface edu.cmu.tetrad.bayes.BayesUpdater
Calculates the updated marginal probabilities of the given node, given the evidence.
calculateUpdatedMarginals(int) - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
Calculates the updated marginal probabilities of the given node, given the evidence.
calculateUpdatedMarginals(int) - Method in class edu.cmu.tetrad.bayes.Identifiability
Calculates the updated marginal probabilities of the given node, given the evidence.
calculateUpdatedMarginals(int) - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Calculates the updated marginal probabilities of the given node, given the evidence.
calculateUpdatedMarginals(int) - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
Calculates the updated marginal probabilities of the given node, given the evidence.
CanCor(double[][], double[][]) - Static method in class edu.cmu.tetrad.search.utils.EstimateRank
Compute canonical correlations from data.
CanCor(int[], int[], double[][]) - Static method in class edu.cmu.tetrad.search.utils.EstimateRank
Compute canonical correlations from covariance matrix.
CaseExpander - Class in edu.cmu.tetrad.data
Makes a new data set in which cases in the given data set that have been assigned multiplicies other than n = 1 are copied out n times.
CaseExpander() - Constructor for class edu.cmu.tetrad.data.CaseExpander
Initializes a new instance of the CaseExpander class.
cauchyCdf(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
Cauchy CDF
cauchyPdf(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
cauchyPdf.
cauchyQuantile(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
cauchyQuantile.
cauchyRand() - Static method in class edu.cmu.tetrad.util.ProbUtils
Cauchy random generator.
cc - Enum constant in enum class edu.cmu.tetrad.graph.EdgeTypeProbability.EdgeType
Circle-to-circle
Ccd - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
CCD (Cyclic Causal Discovery)
Ccd - Class in edu.cmu.tetrad.search
Implemented the Cyclic Causal Discovery (CCD) algorithm by Thomas Richardson.
Ccd() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Ccd
Constructs a new CCD algorithm.
Ccd(IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Ccd
Constructs a new CCD algorithm with the given independence test.
Ccd(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.Ccd
Construct a CCD algorithm with the given independence test.
CCI_SCORE_ALPHA - Static variable in class edu.cmu.tetrad.util.Params
Constant CCI_SCORE_ALPHA="cciScoreAlpha"
CciTest - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Daudin Conditional Independence test.
CciTest() - Constructor for class edu.cmu.tetrad.algcomparison.independence.CciTest
Initializes a new instance of the CciTest class.
CELL_TABLE_TYPE - Static variable in class edu.cmu.tetrad.util.Params
Constant CELL_COUNT_TYPE="cellCountType"
CellTable - Interface in edu.cmu.tetrad.data
Represents a cell table that stores the values of the cells in a table of arbitrary dimension, for use, e.g., in the context of a contingency table--e.g.
CellTableAdTree - Class in edu.cmu.tetrad.data
Stores a cell count table of arbitrary dimension.
CellTableAdTree(DataSet, int[]) - Constructor for class edu.cmu.tetrad.data.CellTableAdTree
Constructs a new CellTableAdTree using the provided data set and test indices.
CellTableAdTree(DataSet, int[], List<Integer>) - Constructor for class edu.cmu.tetrad.data.CellTableAdTree
Constructs a new cell table using the given array for dimensions, initializing all cells in the table to zero.
CellTableCountSample - Class in edu.cmu.tetrad.data
Stores a cell count table of arbitrary dimension.
CellTableCountSample(DataSet, int[]) - Constructor for class edu.cmu.tetrad.data.CellTableCountSample
Constructs a new cell table using the given array for dimensions, initializing all cells in the table to zero.
CellTableCountSample(DataSet, int[], List<Integer>) - Constructor for class edu.cmu.tetrad.data.CellTableCountSample
Constructs a new cell table using the given array for dimensions, initializing all cells in the table to zero.
CellTableProbs - Class in edu.cmu.tetrad.bayes
Estimates probabilities from data by constructing the entire cell count table for the data.
CellTableProbs(DataSet) - Constructor for class edu.cmu.tetrad.bayes.CellTableProbs
Creates a cell count table for the given data set.
center(double[]) - Static method in class edu.cmu.tetrad.data.DataTransforms
center.
center(DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
Subtracts the mean of each column from each datum that column.
center(Matrix) - Static method in class edu.cmu.tetrad.search.FastIca
Centers each row of the given matrix by subtracting the mean of the row from each element.
center(List<DataSet>) - Static method in class edu.cmu.tetrad.data.DataTransforms
center.
centerData(Matrix) - Static method in class edu.cmu.tetrad.data.DataTransforms
centerData.
centeringComp() - Static method in class edu.cmu.tetrad.util.JOptionUtils
centeringComp.
Cfci - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
Conservative FCI.
Cfci - Class in edu.cmu.tetrad.search
Adjusts FCI (see) to use conservative orientation as in CPC (see).
Cfci() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci
Constructs a new conservative FCI algorithm.
Cfci(IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci
Constructs a new conservative FCI algorithm with the given independence test.
Cfci(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.Cfci
Constructs a new FCI search for the given independence test and background knowledge.
CG_EXACT - Static variable in class edu.cmu.tetrad.util.Params
Constant CG_EXACT="cgExact"
changeName(String, String) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
changeName.
changeVariable(Node, Node) - Method in class edu.cmu.tetrad.data.BoxDataSet
Changes the variable for the given column from from to to.
changeVariable(Node, Node) - Method in interface edu.cmu.tetrad.data.DataSet
Changes the variable for the given column from from to to.
changeVariable(Node, Node) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Changes the variable for the given column from from to to.
chebyshev(int, double) - Static method in class edu.cmu.tetrad.util.StatUtils
Computes the value of the Chebyshev polynomial of a given degree at a specified point x.
CHECK_TYPE - Static variable in class edu.cmu.tetrad.util.Params
Constant CHECK_TYPE="checkType"
checkAgainstAndersonDarlingTest(List<Double>) - Method in class edu.cmu.tetrad.search.MarkovCheck
Tests a list of p-values against the Anderson-Darling Test.
checkIndependence(Node, Node, Node...) - Method in interface edu.cmu.tetrad.search.IndependenceTest
Checks the independence fact in question and returns and independence result.
checkIndependence(Node, Node, Node...) - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Checks the independence fact in question and returns and independence result.
checkIndependence(Node, Node, Node...) - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
Checks the independence fact in question and returns and independence result.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.CompositeIndependenceTest
checkIndependence.
checkIndependence(Node, Node, Set<Node>) - Method in interface edu.cmu.tetrad.search.IndependenceTest
checkIndependence.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.IndTestIod
Checks the independence between two nodes given a set of nodes.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Determines whether variable x is independent of variable y given a list of conditioning varNames z.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalCorrelation
Checks the independence of x _||_ y | z
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Returns and independence result that states whether x _||_y | z and what the p-value of the test is.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Returns an independence result specifying whether x _||_ y | Z and what its p-values are.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Determines whether variable x _||_ y | z given a list of conditioning variables z.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
Determines whether x _||_ y | z.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Checks for independence between two nodes given a set of conditioning nodes.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Determines whether variable x is independent of variable y given a list of conditioning varNames z.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Determines whether variable x is independent of variable y given a list of conditioning variables z.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
Checks independence by looking up facts in the list of facts supplied in the constructor.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestMulti
Determines whether variable x is independent of variable y given a list of conditioning variables z.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestMvpLrt
Determines whether two nodes are independent given a set of conditioning nodes.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
checkIndependence.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestRegression
Checks the independence between two variables, given a set of conditioning variables.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Determines independence between variables x and y, given the set of variables z.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.Kci
Checks the independence between two nodes given a set of conditioning variables.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.MsepTest
Checks the independence between two nodes with respect to a set of conditioning nodes.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Checks the independence between two nodes given a set of additional nodes.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Checks the independence between two nodes given a set of conditioning nodes.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Checks the independence between two nodes x and y given a set of conditioning nodes z.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
checkIndependence.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
Checks for independence between two nodes.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMnlrLr
Checks the independence between two nodes given a set of conditioning nodes.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
Checks for independence between two nodes, given a set of conditioning nodes.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Checks the independence between two nodes, given a set of conditioning nodes.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
Checks the independence between two nodes, given a set of conditioning nodes.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
checkIndependence.
checkIndependence(Node, Node, Set<Node>) - Method in class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
Determines the independence between two variables given a set of conditioning variables.
checkIndependenceForTargetNode(Node) - Method in class edu.cmu.tetrad.search.MarkovCheck
Retrieves the list of local independence facts for a given node.
CheckKnowledge - Class in edu.cmu.tetrad.search
Identifies violations of knowledge for a given graph.
checkNestingOfFields() - Method in class edu.cmu.tetrad.util.TetradSerializableUtils
Checks all of the classes in the serialization scope that implement TetradSerializable to make sure all of their fields are either themselves (a) primitive, (b) TetradSerializable, or (c) assignable from types designated as safely serializable by virtue of being included in the safelySerializableTypes array (see), or are arrays whose lowest order component types satisfy either (a), (b), or (c).
checkProbFileExists(String, int, int, int, int, String, int, double, double, String) - Method in class edu.cmu.tetrad.calibration.DataForCalibrationRfci
checkProbFileExists.
checkValue(int) - Method in class edu.cmu.tetrad.data.DiscreteVariable
checkValue.
checkValue(Object) - Method in class edu.cmu.tetrad.data.AbstractVariable
Checks to see whether the passed value can be converted into a value for this variable.
checkValue(Object) - Method in class edu.cmu.tetrad.data.ContinuousVariable
Checks to see whether the passed value can be converted into a value for this variable.
checkValue(Object) - Method in interface edu.cmu.tetrad.data.Variable
Checks to see whether the passed value can be converted into a value for this variable.
CHI_SQUARE - Enum constant in enum class edu.cmu.tetrad.search.test.ChiSquareTest.TestType
The chi-square test.
CHICKERING - Enum constant in enum class edu.cmu.tetrad.search.score.SemBicScore.RuleType
The standard linear, Gaussian BIC score.
chidist(double, int) - Static method in class edu.cmu.tetrad.util.StatUtils
Calculates the one-tail probability of the Chi-squared distribution for doubles
chiSq - Variable in class edu.cmu.tetrad.bayes.BayesProperties.LikelihoodRet
The chi-squared statistic.
chisqCdf(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
chisqCdf.
chisqPdf(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
chisqPdf.
chisqQuantile(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
chisqQuantile.
chisqRand(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
Chi square random generator.
ChiSquare - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Fisher Z test.
ChiSquare - Class in edu.cmu.tetrad.util.dist
Wraps a chi square distribution for purposes of drawing random samples.
ChiSquare - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.IndependenceTestType
Constant for the ChiSquare independence test.
ChiSquare() - Constructor for class edu.cmu.tetrad.algcomparison.independence.ChiSquare
Initializes a new instance of the ChiSquare class.
ChiSquareTest - Class in edu.cmu.tetrad.search.test
Calculates chi-square or g-square for a conditional cross-tabulation table for independence question 0 _||_ 1 | 2, 3, ...max by summing up chi-square and degrees of freedom for each conditional table in turn, where rows or columns that sum to less than a given threshold have been removed.
ChiSquareTest(DataSet, double, ChiSquareTest.TestType, List<Integer>) - Constructor for class edu.cmu.tetrad.search.test.ChiSquareTest
Constructs a test using the given data set and significance level.
ChiSquareTest.CellTableType - Enum Class in edu.cmu.tetrad.search.test
The type of cell table to use.
ChiSquareTest.Result - Class in edu.cmu.tetrad.search.test
Simple class to store the parameters of the result returned by the G Square test.
ChiSquareTest.TestType - Enum Class in edu.cmu.tetrad.search.test
The type of test to perform.
ChoiceGenerator - Class in edu.cmu.tetrad.util
Generates (nonrecursively) all of the combinations of a choose b, where a, b are nonnegative integers and a >= b.
ChoiceGenerator(int, int) - Constructor for class edu.cmu.tetrad.util.ChoiceGenerator
Constructs a new choice generator for a choose b.
cholesky(Matrix) - Static method in class edu.cmu.tetrad.util.MatrixUtils
cholesky.
choleskySimulation(CovarianceMatrix) - Static method in class edu.cmu.tetrad.data.DataUtils
choleskySimulation.
choose(int, int) - Static method in class edu.cmu.tetrad.util.MathUtils
choose.
CIRCLE - Enum constant in enum class edu.cmu.tetrad.graph.Endpoint
Circle endpoint.
circleLayout(Graph) - Static method in class edu.cmu.tetrad.graph.LayoutUtil
Arranges the nodes in the graph in a circle.
ClassifierBayesUpdaterDiscrete - Class in edu.cmu.tetrad.classify
This class contains a method classify which uses an instantiated Bayes net (BayesIm) provided in the constructor.
ClassifierBayesUpdaterDiscrete(BayesIm, DataSet) - Constructor for class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
The constructor sets the values of the private member variables.
ClassifierDiscrete - Interface in edu.cmu.tetrad.classify
Interface implemented by classes that do discrete classification.
ClassifierMbDiscrete - Class in edu.cmu.tetrad.classify
Performs a Bayesian classification of a test set based on a given training set.
ClassifierMbDiscrete(String, String, String, String, String, String, String) - Constructor for class edu.cmu.tetrad.classify.ClassifierMbDiscrete
Constructs a new ClassifierMbDiscrete object using the given training and test data, target variable, alpha value,
classify() - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Computes and returns the cross-tabulation of observed versus estimated values of the target variable as described above.
classify() - Method in interface edu.cmu.tetrad.classify.ClassifierDiscrete
classify.
classify() - Method in class edu.cmu.tetrad.classify.ClassifierMbDiscrete
Classifies the test data by Bayesian updating.
clazz() - Method in class edu.cmu.tetrad.annotation.AnnotatedClass
Gets the class.
clear() - Method in class edu.cmu.tetrad.data.Knowledge
Removes explicit knowledge and tier information.
clear() - Method in class edu.cmu.tetrad.graph.Dag
clear.
clear() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Removes all nodes (and therefore all edges) from the graph.
clear() - Method in interface edu.cmu.tetrad.graph.Graph
Removes all nodes (and therefore all edges) from the graph.
clear() - Method in class edu.cmu.tetrad.graph.LagGraph
clear.
clear() - Method in class edu.cmu.tetrad.graph.SemGraph
clear.
clear() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Clears the graph by removing all vertices and edges.
clear() - Method in class edu.cmu.tetrad.search.MarkovCheck
Clears the results stored in the `resultsIndep` and `resultsDep` lists.
clear() - Method in class edu.cmu.tetrad.util.LogUtils
Removes all streams from logging.
clear() - Method in class edu.cmu.tetrad.util.TetradLogger
Removes all streams from the logger.
clearArchiveDirectory() - Method in class edu.cmu.tetrad.util.TetradSerializableUtils
Clears the archive directory.
clearBookmarks() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Clears all bookmarks.
clearCellTable() - Method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
clearCellTable.
clearEdges() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
clearEdges.
clearEdges() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
clearEdges.
clearEdges() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Removes all edges from the graph.
clearEdges() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Removes all edges from the graph.
clearRow(int, int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Assigns random probability values to the child values of this row that add to 1.
clearRow(int, int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Assigns random probability values to the child values of this row that add to 1.
clearRow(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Clears all values in the specified row of a table.
clearRow(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Assigns random probability values to the child values of this row that add to 1.
clearRow(int, int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Assigns random probability values to the child values of this row that add to 1.
clearSelection() - Method in class edu.cmu.tetrad.data.BoxDataSet
Marks all variables as deselected.
clearSelection() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
clearSelection.
clearSelection() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
clearSelection.
clearSelection() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
clearSelection.
clearSelection() - Method in interface edu.cmu.tetrad.data.DataSet
Marks all variables as deselected.
clearSelection() - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Clears the current selection of variables in the covariance matrix.
clearSelection() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Marks all variables as deselected.
clearTable(int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Randomizes every row in the table for the given node index.
clearTable(int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Randomizes every row in the table for the given node index.
clearTable(int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Clears the table by clearing all rows for the given node.
clearTable(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Randomizes every row in the table for the given node index.
clearTable(int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Randomizes every row in the table for the given node index.
clique(List<Node>) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
True iff the nodes in W form a clique in the current DAG.
Clique - Enum constant in enum class edu.cmu.tetrad.search.utils.ClusterSignificance.CheckType
Check to see if the cluster is a clique.
cliques(Graph) - Method in class edu.cmu.tetrad.sem.Ricf
cliques.
clone() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.BiolinguaDigraph
Returns a clone of this graph
clone() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Digraph
Returns a clone of this graph
clone() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Returns a clone of this graph
cluster(Matrix) - Method in interface edu.cmu.tetrad.cluster.ClusteringAlgorithm
Clusters the given data set.
cluster(Matrix) - Method in class edu.cmu.tetrad.cluster.KMeans
Clusters the given data set.
ClusterAlgorithm - Interface in edu.cmu.tetrad.algcomparison.algorithm.cluster
Tags an algorithm that generates clusters.
ClusteringAlgorithm - Interface in edu.cmu.tetrad.cluster
Represents a clustering algorithm to cluster some data.
Clusters - Class in edu.cmu.tetrad.data
Stores clusters of variables for MimBuild, Purify, etc.
Clusters() - Constructor for class edu.cmu.tetrad.data.Clusters
Constructs a blank knowledge object.
Clusters(Clusters) - Constructor for class edu.cmu.tetrad.data.Clusters
Copy constructor.
ClusterSignificance - Class in edu.cmu.tetrad.search.utils
Provides some methods to check significance of clusters for clustering algroithms.
ClusterSignificance(List<Node>, DataModel) - Constructor for class edu.cmu.tetrad.search.utils.ClusterSignificance
Constructs a new cluster significance object.
ClusterSignificance.CheckType - Enum Class in edu.cmu.tetrad.search.utils
Gives the options for checking significance of clusters--could check the significance using a regression model, or could check to see if the cluster is a clique, or could not do the check.
clustersToPartition(Clusters, List<Node>) - Static method in class edu.cmu.tetrad.search.utils.ClusterUtils
Converts a list of indices into a list of Nodes representing a cluster.
ClusterUtils - Class in edu.cmu.tetrad.search.utils
Provides some general utilities for dealing with clustering input and output.
COEF - Enum constant in enum class edu.cmu.tetrad.sem.ParamType
Enum representing the free parameter type for structural equation modeling (SEM) models.
COEF_HIGH - Static variable in class edu.cmu.tetrad.util.Params
Constant COEF_HIGH="coefHigh"
COEF_LOW - Static variable in class edu.cmu.tetrad.util.Params
Constant COEF_LOW="coefLow"
COEF_SYMMETRIC - Static variable in class edu.cmu.tetrad.util.Params
Constant COEF_SYMMETRIC="coefSymmetric"
collider(Node, Node, Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns true iff [a, b, c] is a collider.
COLLIDER - Enum constant in enum class edu.cmu.tetrad.search.utils.GraphSearchUtils.CpcTripleType
A collider triple.
COLLIDER - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.VcPc.CpcTripleType
The triple is a collider.
COLLIDER - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.VcPcFast.CpcTripleType
Constant COLLIDER
COLLIDER_DISCOVERY_RULE - Static variable in class edu.cmu.tetrad.util.Params
Constant COLLIDER_DISCOVERY_RULE="colliderDiscoveryRule"
colliderAllowed(Graph, Node, Node, Node, Knowledge) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Determines if the collider is allowed.
colliderAllowed(Graph, Node, Node, Node, Knowledge) - Static method in class edu.cmu.tetrad.search.utils.PcCommon
Checks if colliders are allowed based on the given knowledge.
colliderOrientedMsg(Node, Node, Node) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
colliderOrientedMsg.
colliderOrientedMsg(Node, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
colliderOrientedMsg.
colliderOrientedMsg(String, Node, Node, Node) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
colliderOrientedMsg.
colMax(DoubleMatrix2D) - Static method in class edu.pitt.csb.mgm.MixedUtils
return vector of the maximum of each column in m (as ints, i.e.
COLON - Static variable in class edu.cmu.tetrad.data.DelimiterType
Constant COLON
columnCount() - Method in interface edu.pitt.isp.sverchkov.data.DataTable
columnCount.
columnCount() - Method in class edu.pitt.isp.sverchkov.data.DataTableImpl
columnCount.
CombinationGenerator - Class in edu.cmu.tetrad.util
Generates (nonrecursively) all of the combinations of objects, where the number of objects in each dimension is specified.
CombinationGenerator(int[]) - Constructor for class edu.cmu.tetrad.util.CombinationGenerator
Constructs a new combination of objects, choosing one object from each dimension.
CombinationIterator - Class in edu.cmu.tetrad.util
Iterates through all the posible combinations for a set of variables (each with a different number of possible values).
CombinationIterator(int[]) - Constructor for class edu.cmu.tetrad.util.CombinationIterator
Creates a combination set for a set of variables with the given number of maxValues
combineContinuousData(List<DataModel>, double[][]) - Static method in class edu.cmu.tetrad.util.MultidataUtils
combineContinuousData.
combineDataset(List<DataModel>) - Static method in class edu.cmu.tetrad.util.MultidataUtils
combineDataset.
combineDiscreteDataToDiscreteVerticalData(List<DataModel>, List<Node>, int[][], int, int) - Static method in class edu.cmu.tetrad.util.MultidataUtils
combineDiscreteDataToDiscreteVerticalData.
combineMixedContinuousData(List<DataModel>, List<Node>, double[][], int, int) - Static method in class edu.cmu.tetrad.util.MultidataUtils
combineMixedContinuousData.
combineMixedDiscreteData(List<DataModel>, List<Node>, int[][], int, int) - Static method in class edu.cmu.tetrad.util.MultidataUtils
combineMixedDiscreteData.
combineVariables(List<DataModel>, List<Node>) - Static method in class edu.cmu.tetrad.util.MultidataUtils
Combine the list of variables from each of data model in the list into one variable list.
COMMA - Enum constant in enum class edu.cmu.tetrad.calculator.parser.Token
Comma.
COMMA - Enum constant in enum class edu.cmu.tetrad.util.TextTable.Delimiter
Constant COMMA
COMMA - Static variable in class edu.cmu.tetrad.data.DelimiterType
Constant COMMA
command() - Element in annotation interface edu.cmu.tetrad.annotation.Algorithm
Command of the algorithm.
command() - Element in annotation interface edu.cmu.tetrad.annotation.Score
The command to execute the score.
command() - Element in annotation interface edu.cmu.tetrad.annotation.TestOfIndependence
Command of the test.
CommonAncestorFalseNegativeBidirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
CommonAncestorFalseNegativeBidirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalseNegativeBidirected
Constructs a new instance of the statistic.
CommonAncestorFalsePositiveBidirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
CommonAncestorFalsePositiveBidirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalsePositiveBidirected
Constructs a new instance of the statistic.
CommonAncestorTruePositiveBidirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
CommonAncestorTruePositiveBidirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorTruePositiveBidirected
Constructs a new instance of the statistic.
CommonMeasuredAncestorRecallBidirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
CommonMeasuredAncestorRecallBidirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.CommonMeasuredAncestorRecallBidirected
Initializes a new instance of the CommonMeasuredAncestorRecallBidirected class.
compare(ComparisonParameters) - Static method in class edu.cmu.tetrad.study.performance.Comparison
Simulates data from model paramerizing the given DAG, and runs the algorithm on that data, printing out error statistics.
compare(ComparisonParameters) - Static method in class edu.cmu.tetrad.study.performance.Comparison2
Simulates data from model parameterizing the given DAG, and runs the algorithm on that data, printing out error statistics.
COMPARE_GRAPH_ALGCOMP - Static variable in class edu.cmu.tetrad.util.Params
Constant USE_PSEUDOINVERSE_FOR_LATENT="usePseudoinverseForLatent"
compareFromFiles(String, Algorithms, Statistics, Parameters) - Method in class edu.cmu.tetrad.algcomparison.Comparison
compareFromFiles.
compareFromFiles(String, Algorithms, Statistics, Parameters, long, TimeUnit) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
compareFromFiles.
compareFromFiles(String, String, Algorithms, Statistics, Parameters) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Compares algorithms.
compareFromFiles(String, String, Algorithms, Statistics, Parameters, long, TimeUnit) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
Compares algorithms.
compareFromSimulations(String, Simulations, Algorithms, Statistics, Parameters) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Compare simulation results using the provided parameters and write the comparison results to a file.
compareFromSimulations(String, Simulations, Algorithms, Statistics, Parameters, long, TimeUnit) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
compareFromSimulations.
compareFromSimulations(String, Simulations, String, Algorithms, Statistics, Parameters) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Compares the results obtained from simulations.
compareFromSimulations(String, Simulations, String, Algorithms, Statistics, Parameters, long, TimeUnit) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
Compares algorithms.
compareFromSimulations(String, Simulations, String, PrintStream, Algorithms, Statistics, Parameters) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Compares the results of simulations and generates an output file.
compareFromSimulations(String, Simulations, String, PrintStream, PrintStream, Algorithms, Statistics, Parameters) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Compares the results of different simulations and algorithms.
compareTo(Edge) - Method in class edu.cmu.tetrad.graph.Edge
compareTo.
compareTo(IndependenceFact) - Method in class edu.cmu.tetrad.graph.IndependenceFact
Note that this compareTo method gives a lexical ordering for independence facts and doesn't reflect independence fact equality.
compareTo(Node) - Method in interface edu.cmu.tetrad.graph.Node
Returns the hashcode for this node.
compareTo(ScoredGraph) - Method in class edu.cmu.tetrad.search.score.ScoredGraph
Returns a compare value for this scored graph compared ot the given scored graph.
compareTo(Bes.Arrow) - Method in class edu.cmu.tetrad.search.utils.Bes.Arrow
Sorting by bump, high to low.
compareTo(Point) - Method in class edu.cmu.tetrad.util.Point
True iff the given object is a point with the same coordinates as this one.
compareTo(Object) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch.Gene
compareTo(Object) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedFactor
CompareTwoGraphs - Class in edu.cmu.tetrad.algcomparison
Gives the comparison of a target graph to a reference graph that is implemented in the interface.
Comparison - Class in edu.cmu.tetrad.algcomparison
Script to do a comparison of a list of algorithms using a list of statistics and a list of parameters and their values.
Comparison - Class in edu.cmu.tetrad.study.performance
Does a comparison of algorithm results across algorithm type, sample sizes, etc.
Comparison() - Constructor for class edu.cmu.tetrad.algcomparison.Comparison
Initializes a new instance of the Comparison class.
Comparison.ComparisonGraph - Enum Class in edu.cmu.tetrad.algcomparison
An enum of comparison graphs types.
Comparison.TableColumn - Enum Class in edu.cmu.tetrad.study.performance
An enumeration of the columns in the comparison table.
Comparison2 - Class in edu.cmu.tetrad.study.performance
Does a comparison of algorithm results across algorithm type, sample sizes, etc.
Comparison2.TableColumn - Enum Class in edu.cmu.tetrad.study.performance
An enum of table columns.
ComparisonParameters - Class in edu.cmu.tetrad.study.performance
Created by jdramsey on 3/24/16.
ComparisonParameters() - Constructor for class edu.cmu.tetrad.study.performance.ComparisonParameters
Constructor for ComparisonParameters.
ComparisonParameters(ComparisonParameters) - Constructor for class edu.cmu.tetrad.study.performance.ComparisonParameters
Constructor for ComparisonParameters.
ComparisonParameters.Algorithm - Enum Class in edu.cmu.tetrad.study.performance
An enumeration of the algorithms that can be used for structure learning.
ComparisonParameters.DataType - Enum Class in edu.cmu.tetrad.study.performance
An enumeration of the data types that can be used for structure learning.
ComparisonParameters.IndependenceTestType - Enum Class in edu.cmu.tetrad.study.performance
An enumeration of the independence test types that can be used for structure learning.
ComparisonParameters.ResultType - Enum Class in edu.cmu.tetrad.study.performance
An enumeration of the result types that can be used for structure learning.
ComparisonResult - Class in edu.cmu.tetrad.study.performance
.
ComparisonResult(ComparisonParameters) - Constructor for class edu.cmu.tetrad.study.performance.ComparisonResult
Constructor for ComparisonResult.
ComparisonScript - Class in edu.cmu.tetrad.study.performance
Runs algorithm on data set (simulation is OK), printing out error statistics.
compatible(Edge, Edge) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Determines if two edges are compatible.
COMPLETE_RULE_SET_USED - Static variable in class edu.cmu.tetrad.util.Params
Constant COMPLETE_RULE_SET_USED="completeRuleSetUsed"
completeGraph(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
completeGraph.
CompositeIndependenceTest - Class in edu.cmu.tetrad.search
CompositeIndependenceTest class.
CompositeIndependenceTest(IndependenceTest[]) - Constructor for class edu.cmu.tetrad.search.CompositeIndependenceTest
Constructor for CompositeIndependenceTest.
composition() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Checks if composition holds--e.g., (X ⊥⊥ Y | Z) ∧ (X ⊥⊥ W |Z) ==> X ⊥⊥ (Y ∪ W) |Z
compositionalGraphoid() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Checks whether the IM is a compositional graphoid.
compressedCorrelation(Vector, Vector) - Static method in class edu.cmu.tetrad.util.StatUtils
compressedCorrelation.
compute(boolean) - Method in interface edu.cmu.tetrad.stat.correlation.Covariance
compute.
compute(boolean) - Method in class edu.cmu.tetrad.stat.correlation.CovarianceMatrix
compute.
compute(boolean) - Method in interface edu.cmu.tetrad.stat.correlation.RealCovariance
compute.
compute(boolean) - Method in class edu.cmu.tetrad.stat.correlation.RealCovarianceMatrix
compute.
compute(boolean) - Method in class edu.cmu.tetrad.stat.correlation.RealCovarianceMatrixForkJoin
compute.
compute(boolean) - Method in interface edu.cmu.tetrad.stat.RealVariance
compute.
compute(boolean) - Method in class edu.cmu.tetrad.stat.RealVarianceVector
compute.
compute(boolean) - Method in class edu.cmu.tetrad.stat.RealVarianceVectorForkJoin
compute.
compute(boolean) - Method in interface edu.cmu.tetrad.stat.Variance
compute.
compute(boolean) - Method in class edu.cmu.tetrad.stat.VarianceVector
compute.
compute(boolean) - Method in class edu.cmu.tetrad.stat.VarianceVectorForkJoin
compute.
computeLowerTriangle(boolean) - Method in interface edu.cmu.tetrad.stat.correlation.Covariance
computeLowerTriangle.
computeLowerTriangle(boolean) - Method in class edu.cmu.tetrad.stat.correlation.CovarianceMatrix
computeLowerTriangle.
computeLowerTriangle(boolean) - Method in interface edu.cmu.tetrad.stat.correlation.RealCovariance
computeLowerTriangle.
computeLowerTriangle(boolean) - Method in class edu.cmu.tetrad.stat.correlation.RealCovarianceMatrix
computeLowerTriangle.
computeLowerTriangle(boolean) - Method in class edu.cmu.tetrad.stat.correlation.RealCovarianceMatrixForkJoin
computeLowerTriangle.
computeStdErrors(ISemIm) - Method in class edu.cmu.tetrad.sem.SemStdErrorEstimator
This method computes the information matrix or Hessian matrix of second order partial derivatives of the fitting function (4B_2 on page 135 of Bollen) with respect to the free freeParameters of the estimated SEM.
concatenate(double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Concatenates the vectors rows[i], i = 0...rows.length, into a single vector.
concatenate(DataSet...) - Static method in class edu.cmu.tetrad.data.DataTransforms
concatenate.
concatenate(DataSet, DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
concatenate.
concatenate(Matrix...) - Static method in class edu.cmu.tetrad.data.DataTransforms
concatenate.
concatenate(List<DataSet>) - Static method in class edu.cmu.tetrad.data.DataTransforms
concatenate.
CONCURRENT_FAS - Static variable in class edu.cmu.tetrad.util.Params
Constant CONCURRENT_FAS="concurrentFAS"
CONDITIONAL_GAUSSIAN - Static variable in class edu.cmu.tetrad.algcomparison.simulation.SimulationTypes
Constant CONDITIONAL_GAUSSIAN="Mixed Conditional Gaussian"
ConditionalCorrelationIndependence - Class in edu.cmu.tetrad.search.test
Checks conditional independence of variable in a continuous data set using Daudin's method.
ConditionalCorrelationIndependence(DataSet, int, double, int) - Constructor for class edu.cmu.tetrad.search.test.ConditionalCorrelationIndependence
Initializes a new instance of the ConditionalCorrelationIndependence class using the provided DataSet.
ConditionalGaussianBicScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for Fisher Z test.
ConditionalGaussianBicScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.ConditionalGaussianBicScore
Initializes a new instance of the FisherZ class.
ConditionalGaussianLikelihood - Class in edu.cmu.tetrad.search.score
Implements a conditional Gaussian likelihood.
ConditionalGaussianLikelihood(DataSet) - Constructor for class edu.cmu.tetrad.search.score.ConditionalGaussianLikelihood
Constructs the score using a covariance matrix.
ConditionalGaussianLikelihood.Ret - Class in edu.cmu.tetrad.search.score
Gives return value for a conditional Gaussian likelihood, returning a likelihood value and the degrees of freedom for it.
ConditionalGaussianLRT - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Fisher Z test.
ConditionalGaussianLRT() - Constructor for class edu.cmu.tetrad.algcomparison.independence.ConditionalGaussianLRT
Initializes a new instance of the FisherZ class.
ConditionalGaussianScore - Class in edu.cmu.tetrad.search.score
Implements a conditional Gaussian BIC score for FGS, which calculates a BIC score for mixed discrete/Gaussian data using the conditional Gaussian likelihood function (see).
ConditionalGaussianScore(DataSet, double, boolean) - Constructor for class edu.cmu.tetrad.search.score.ConditionalGaussianScore
Constructs the score using a covariance matrix.
ConditionalGaussianSimulation - Class in edu.cmu.tetrad.algcomparison.simulation
A simulation method based on the conditional Gaussian assumption.
ConditionalGaussianSimulation(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Constructor for ConditionalGaussianSimulation.
ConditioningSetType - Enum Class in edu.cmu.tetrad.search
The type of conditioning set to use for the Markov check.
config(String) - Method in class edu.cmu.tetrad.util.LogUtils
config.
configuration(String) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Generates a configuration file containing information about available algorithms, statistics, independence tests, scores, and simulations.
configuration(String) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
configuration.
configurationActivated(TetradLoggerEvent) - Method in interface edu.cmu.tetrad.util.TetradLoggerListener
Invoked whenever a logger configuration is set on the TetradLogger and the logger is active (i.e., logging isn't turned off etc).
configurationDeactivated(TetradLoggerEvent) - Method in interface edu.cmu.tetrad.util.TetradLoggerListener
Invoked whenever a previously set logger config is resert or set to null and the logger is active (i.e., logging isn't turned off etc).
CONFLICT_RULE - Static variable in class edu.cmu.tetrad.util.Params
Constant CONFLICT_RULE="conflictRule"
CONNECTED - Static variable in class edu.cmu.tetrad.util.Params
Constant CONNECTED="connected"
CONNECTED_DAG - Static variable in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Connected DAG uniformly selected
connectedComponents() - Method in class edu.cmu.tetrad.graph.Paths
Returns a list of connected components in the graph.
ConnectionFunction - Interface in edu.cmu.tetrad.sem
Created by IntelliJ IDEA.
CONSERVATIVE - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.ColliderDiscovery
FAS with conservative reasoning.
CONSTANT - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Constant CONSTANT=0
CONSTANT - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.history.SimpleRandomizer
Indicates constant indegree.
ConstantExpression - Class in edu.cmu.tetrad.calculator.expression
Represents a constant expression, that is an expression that always evaluates to the same value.
ConstantExpression(double) - Constructor for class edu.cmu.tetrad.calculator.expression.ConstantExpression
Constructs the constant expression given the value to use.
constructCentralizedGramMatrix(List<Kernel>, DataSet, List<Node>) - Static method in class edu.cmu.tetrad.search.utils.KernelUtils
Constructs the centralized Gram matrix for a given vector valued sample.
constructGramMatrix(List<Kernel>, DataSet, List<Node>) - Static method in class edu.cmu.tetrad.search.utils.KernelUtils
Constructs Gram matrix for a given vector valued sample.
constructH(int) - Static method in class edu.cmu.tetrad.search.utils.KernelUtils
Constructs the projection matrix on 1/m
contains(GraphChange) - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Contains is defined such that if the internal strucs of this GraphChange all individually contain the elements in the corresponding strucs of GraphChange gc, then this "contains" gc.
containsBidirectedEdge(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Checks if a given graph contains a bidirected edge.
containsEdge(KnowledgeEdge) - Method in class edu.cmu.tetrad.data.KnowledgeGroup
containsEdge.
containsEdge(Edge) - Method in class edu.cmu.tetrad.graph.Dag
Checks if the given edge is present in the graph.
containsEdge(Edge) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Determines whether this graph contains the given edge.
containsEdge(Edge) - Method in interface edu.cmu.tetrad.graph.Graph
Determines whether this graph contains the given edge.
containsEdge(Edge) - Method in class edu.cmu.tetrad.graph.LagGraph
Determines whether this graph contains the given edge.
containsEdge(Edge) - Method in class edu.cmu.tetrad.graph.SemGraph
Determines whether this graph contains the given edge.
containsEdge(Edge) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Checks if the given Edge object exists in the graph.
containsEmptyData() - Method in class edu.cmu.tetrad.data.DataModelList
Use this to check if the dataModelList only contains the default empty dataset that is being used to populat the empty spreadsheet - Added by Kevin
containsLatent(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch.LatentStructure
containsLatent.
containsMissingValue(DataSet) - Static method in class edu.cmu.tetrad.data.DataUtils
containsMissingValue.
containsMissingValue(Matrix) - Static method in class edu.cmu.tetrad.data.DataUtils
containsMissingValue.
containsNode(Node) - Method in class edu.cmu.tetrad.graph.Dag
Checks if the given Node object is contained in the graph.
containsNode(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Determines whether this graph contains the given node.
containsNode(Node) - Method in interface edu.cmu.tetrad.graph.Graph
Determines whether this graph contains the given node.
containsNode(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Determines whether this graph contains the given node.
containsNode(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Determines whether this graph contains the given node.
containsNode(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Checks if the graph contains a specific node.
containsParameter(Edge) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
containsParameter.
Context - Interface in edu.cmu.tetrad.calculator.expression
Looks up the value of a variable.
Continuous - Enum constant in enum class edu.cmu.tetrad.data.DataType
Continuous.
Continuous - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.DataType
Constant for continuous data.
ContinuousDiscretizationSpec - Class in edu.cmu.tetrad.data
Specifies how a column (continuous or discrete) should be discretized.
ContinuousDiscretizationSpec(double[], List<String>) - Constructor for class edu.cmu.tetrad.data.ContinuousDiscretizationSpec
Constructor for creating a ContinuousDiscretizationSpec object.
ContinuousDiscretizationSpec(double[], List<String>, int) - Constructor for class edu.cmu.tetrad.data.ContinuousDiscretizationSpec
Creates a ContinuousDiscretizationSpec object with the given breakpoints, categories, and method.
ContinuousVariable - Class in edu.cmu.tetrad.data
Represents a real-valued variable.
ContinuousVariable(ContinuousVariable) - Constructor for class edu.cmu.tetrad.data.ContinuousVariable
Copy constructor.
ContinuousVariable(String) - Constructor for class edu.cmu.tetrad.data.ContinuousVariable
Constructs a new continuous variable with the given name.
contraction() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Checks if contraction holds--e.g., (X ⊥⊥ Y |Z) ∧ (X ⊥⊥ W |Z ∪ Y) ==> X ⊥⊥ (Y ∪ W) |Z
convert() - Method in class edu.cmu.tetrad.search.utils.DagToPag
This method does the conversion of DAG to PAG.
convert() - Method in class edu.cmu.tetrad.search.utils.TsDagToPag
convert.
convert(String) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts a string spec of a graph--for example, "X1-->X2, X1---X3, X2o->X4, X3<->X4" to a Graph.
convertCovToCorr(Matrix) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Converts a covariance matrix to a correlation matrix in place; the same matrix is returned for convenience, but m is modified in the process.
convertListToInt(List<List<Node>>, List<Node>) - Static method in class edu.cmu.tetrad.search.utils.ClusterUtils
Converts a list of indices into a list of Nodes representing a cluster.
convertLowerTriangleToSymmetric(double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Converts a matrix in lower triangular form to a symmetric matrix in square form.
convertNodes(Set<Edge>, List<Node>) - Static method in class edu.cmu.tetrad.graph.MisclassificationUtils
convertNodes.
convertNumericalDiscreteToContinuous(DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
convertNumericalDiscreteToContinuous.
convertSearchGraph(SemGraph) - Static method in class edu.cmu.tetrad.search.utils.Purify
convertSearchGraph.
convertSearchGraph(List<int[]>, String[]) - Static method in class edu.cmu.tetrad.search.utils.ClusterUtils
Converts a list of indices into a list of Nodes representing a cluster.
convertTo1DArray(SimpleMatrix) - Static method in class edu.cmu.tetrad.search.test.Kci
Converts a SimpleMatrix to a 1D array.
convertToClusters(Graph) - Static method in class edu.cmu.tetrad.search.utils.MimUtils
convertToClusters.
convertToClusters(Graph, List<Node>) - Static method in class edu.cmu.tetrad.search.utils.MimUtils
Converts a disconnected multiple indicator model into a set of clusters.
convertToClusters2(Graph) - Static method in class edu.cmu.tetrad.search.utils.MimUtils
convertToClusters2.
convertToXml(Graph) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
convertToXml.
ConvexProximal - Class in edu.pitt.csb.mgm
This interface should be used for non-differentiable convex functions that are decomposable such that f(x) = g(x) + h(x) where g(x) is a differentiable convex function (i.e.
ConvexProximal() - Constructor for class edu.pitt.csb.mgm.ConvexProximal
Constructor for ConvexProximal.
copy() - Method in class edu.cmu.tetrad.data.BoxDataSet
Returns a copy of this dataset.
copy() - Method in class edu.cmu.tetrad.data.ByteDataBox
copy.
copy() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
copy.
copy() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
copy.
copy() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
copy.
copy() - Method in interface edu.cmu.tetrad.data.DataBox
copy.
copy() - Method in interface edu.cmu.tetrad.data.DataModel
copy.
copy() - Method in class edu.cmu.tetrad.data.DataModelList
copy.
copy() - Method in interface edu.cmu.tetrad.data.DataSet
Returns a copy of this dataset.
copy() - Method in class edu.cmu.tetrad.data.DoubleDataBox
copy.
copy() - Method in class edu.cmu.tetrad.data.FloatDataBox
copy.
copy() - Method in class edu.cmu.tetrad.data.IndependenceFacts
copy.
copy() - Method in class edu.cmu.tetrad.data.IntDataBox
copy.
copy() - Method in class edu.cmu.tetrad.data.Knowledge
Makes a shallow copy.
copy() - Method in class edu.cmu.tetrad.data.LongDataBox
copy.
copy() - Method in class edu.cmu.tetrad.data.MixedDataBox
copy.
copy() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Returns a copy of this dataset.
copy() - Method in class edu.cmu.tetrad.data.ShortDataBox
copy.
copy() - Method in class edu.cmu.tetrad.data.TimeSeriesData
copy.
copy() - Method in class edu.cmu.tetrad.data.VerticalDoubleDataBox
copy.
copy() - Method in class edu.cmu.tetrad.data.VerticalIntDataBox
copy.
copy() - Method in class edu.cmu.tetrad.util.DefaultTetradLoggerConfig
copy.
copy() - Method in class edu.cmu.tetrad.util.Matrix
copy.
copy() - Method in class edu.cmu.tetrad.util.TetradLogger.EmptyConfig
copy.
copy() - Method in interface edu.cmu.tetrad.util.TetradLoggerConfig
Creates a copy of the TetradLoggerConfig object.
copy() - Method in class edu.cmu.tetrad.util.Vector
copy.
copy() - Method in class edu.pitt.csb.stability.DataGraphSearch
copy.
copy() - Method in class edu.pitt.csb.stability.SearchWrappers.FgesWrapper
Copy constructor.
copy() - Method in class edu.pitt.csb.stability.SearchWrappers.MGMWrapper
Copy constructor.
copy() - Method in class edu.pitt.csb.stability.SearchWrappers.PcStableWrapper
Copy constructor.
copyColumn(Node, DataSet, DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
copyColumn.
copyOf(double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
copyOf.
copyOf(int[], int) - Static method in class edu.cmu.tetrad.util.MatrixUtils
copyOf.
corr(Node, Node, List<Node>) - Method in class edu.cmu.tetrad.search.utils.PartialCorrelation
Calculates the partial correlation of x and y conditional on the nodes in z recursively.
correctnessRatio(int[][]) - Static method in class edu.cmu.tetrad.simulation.HsimUtils
correctnessRatio.
CorrectSkeleton - Class in edu.cmu.tetrad.algcomparison.statistic
Outputs 1 if the skeleton is correct, 0 if not..
CorrectSkeleton() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.CorrectSkeleton
Initializes a new instance of the CorrectSkeleton class.
correlation(double[], double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
correlation.
correlation(double[], double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
correlation.
correlation(long[], long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
correlation.
correlation(long[], long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
correlation.
correlation(Vector, Vector) - Static method in class edu.cmu.tetrad.util.StatUtils
correlation.
CorrelationMatrix - Class in edu.cmu.tetrad.data
Stores a correlation matrix together with variable names and sample size; intended as a representation of a data set.
CorrelationMatrix(DataSet) - Constructor for class edu.cmu.tetrad.data.CorrelationMatrix
Constructs a new correlation matrix from the the given DataSet.
CorrelationMatrix(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.data.CorrelationMatrix
Constructs a new correlation matrix using the covariances in the given covariance matrix.
CorrelationMatrix(List<Node>, Matrix, int) - Constructor for class edu.cmu.tetrad.data.CorrelationMatrix
Constructs a correlation matrix data set using the given information.
CorrelationMatrixOnTheFly - Class in edu.cmu.tetrad.data
Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
CorrelationMatrixOnTheFly(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Constructs a new covariance matrix from the given data set.
corrExp(double[], double[], double[]) - Static method in class edu.cmu.tetrad.search.Fask
Calculates the expected correlation between two arrays of double values where z is positive.
count(Map<A, V>) - Method in class edu.pitt.isp.sverchkov.data.AdTree
Returns the number of rows in the data set.
COUNT_MAP - Enum constant in enum class edu.cmu.tetrad.bayes.MlBayesIm.CptMapType
Represents a count-based CptMap type.
COUNT_SAMPLE - Enum constant in enum class edu.cmu.tetrad.search.test.ChiSquareTest.CellTableType
The count sample cell table.
countAdjErrors(Graph, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Counts the adjacencies that are in graph1 but not in graph2.
countColumn(File, char) - Static method in class edu.cmu.tetrad.util.DataUtility
countColumn.
countLine(File) - Static method in class edu.cmu.tetrad.util.DataUtility
countLine.
counts(A, Map<A, V>) - Method in class edu.pitt.isp.sverchkov.data.AdTree
Returns the number of rows in the data set.
cov() - Method in record class edu.cmu.tetrad.search.score.SemBicScore.CovAndCoefs
Returns the value of the cov record component.
cov(double[], double[], double[], double, double) - Static method in class edu.cmu.tetrad.util.StatUtils
cov.
cov(Matrix) - Static method in class edu.cmu.tetrad.data.DataUtils
cov.
COV_HIGH - Static variable in class edu.cmu.tetrad.util.Params
Constant COV_HIGH="covHigh"
COV_LOW - Static variable in class edu.cmu.tetrad.util.Params
Constant COV_LOW="covLow"
COV_SYMMETRIC - Static variable in class edu.cmu.tetrad.util.Params
Constant COV_SYMMETRIC="covSymmetric"
CovAndCoefs(Matrix, Matrix) - Constructor for record class edu.cmu.tetrad.search.score.SemBicScore.CovAndCoefs
Creates an instance of a CovAndCoefs record class.
COVAR - Enum constant in enum class edu.cmu.tetrad.sem.ParamType
Represents a free parameter type for structural equation modeling (SEM) models.
covariance(double[], double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
covariance.
covariance(double[], double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
covariance.
covariance(int, int) - Method in interface edu.cmu.tetrad.data.Covariances
Returns the covariance at (i, j).
covariance(int, int) - Method in class edu.cmu.tetrad.data.CovariancesDoubleForkJoin
covariance.
covariance(long[], long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
covariance.
covariance(long[], long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
covariance.
Covariance - Enum constant in enum class edu.cmu.tetrad.data.DataType
Covariance.
Covariance - Interface in edu.cmu.tetrad.stat.correlation
Interface for computing covariances.
CovarianceMatrix - Class in edu.cmu.tetrad.data
Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
CovarianceMatrix - Class in edu.cmu.tetrad.stat.correlation
Jan 25, 2016 2:13:26 PM
CovarianceMatrix(float[][]) - Constructor for class edu.cmu.tetrad.stat.correlation.CovarianceMatrix
Constructor for CovarianceMatrix.
CovarianceMatrix(CovarianceMatrix) - Constructor for class edu.cmu.tetrad.data.CovarianceMatrix
Copy constructor.
CovarianceMatrix(DataSet) - Constructor for class edu.cmu.tetrad.data.CovarianceMatrix
Constructs a new covariance matrix from the given data set.
CovarianceMatrix(DataSet, boolean) - Constructor for class edu.cmu.tetrad.data.CovarianceMatrix
Constructor for CovarianceMatrix.
CovarianceMatrix(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.data.CovarianceMatrix
Constructor for CovarianceMatrix.
CovarianceMatrix(List<Node>, double[][], int) - Constructor for class edu.cmu.tetrad.data.CovarianceMatrix
Constructor for CovarianceMatrix.
CovarianceMatrix(List<Node>, Matrix, int) - Constructor for class edu.cmu.tetrad.data.CovarianceMatrix
Protected constructor to construct a new covariance matrix using the supplied continuous variables and the the given symmetric, positive definite matrix and sample size.
CovarianceMatrixOnTheFly - Class in edu.cmu.tetrad.data
Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
CovarianceMatrixOnTheFly(DataSet) - Constructor for class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Constructs a new covariance matrix from the given data set.
CovarianceMatrixOnTheFly(DataSet, boolean) - Constructor for class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Constructor for CovarianceMatrixOnTheFly.
covarianceNonparanormalDrton(DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
covarianceNonparanormalDrton.
Covariances - Interface in edu.cmu.tetrad.data
Some comemon methods for the various covariance implementations.
CovariancesDoubleForkJoin - Class in edu.cmu.tetrad.data
Computes covariances using the standard calculation.
CovariancesDoubleForkJoin(double[][], boolean) - Constructor for class edu.cmu.tetrad.data.CovariancesDoubleForkJoin
Constructor for CovariancesDoubleForkJoin.
covered(SortedSet<ItkPredictorSearch.Gene>, SortedSet<ItkPredictorSearch.Gene>) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch
covered.
coveredEdge(Node, Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns true iff x->y or y->x is a covered edge.
covMatrix(double[], double[], double[][], double[], double, double) - Static method in class edu.cmu.tetrad.util.StatUtils
covMatrix.
Cpc - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
Conservative PC (CPC).
Cpc - Class in edu.cmu.tetrad.search
Implements a convervative version of PC, in which the Markov condition is assumed but faithfulness is tested locally.
Cpc() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cpc
This class represents the constructor for the Cpc class.
Cpc(IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cpc
This class represents the constructor for the Cpc class.
Cpc(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.Cpc
Constructs a CPC algorithm that uses the given independence test as oracle.
CPC - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.Algorithm
Constant for the CPC algorithm.
CPDAG - Enum constant in enum class edu.cmu.tetrad.graph.GraphUtils.GraphType
The CPDAG graph type.
CPDAG - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.ResultType
Constant for CPDAG result type.
CPDAG - Static variable in class edu.cmu.tetrad.util.Params
Constant CPDAG="cpdag"
CPDAG_of_the_true_DAG - Enum constant in enum class edu.cmu.tetrad.algcomparison.Comparison.ComparisonGraph
Constant for the CPDAG of the true DAG.
CPDAG_of_the_true_DAG - Enum constant in enum class edu.cmu.tetrad.algcomparison.TimeoutComparison.ComparisonGraph
The cpdag of the true dag.
CpdagParentDistancesFromTrue - Class in edu.cmu.tetrad.search
CpdagParentDistancesFromTrue computes the distances between true edge strengths in a true DAG and the range of estimated edge strengths in an output CPDAG.
CpdagParentDistancesFromTrue() - Constructor for class edu.cmu.tetrad.search.CpdagParentDistancesFromTrue
Constructs a new instance of the class.
CpdagParentDistancesFromTrue.DistanceType - Enum Class in edu.cmu.tetrad.search
The type of distance to calculate.
CptInvariantMarginalCalculator - Class in edu.cmu.tetrad.bayes
Calculates marginals of the form P(V=v') for an updated Bayes net for purposes of the CPT Invariant Updater.
CptInvariantMarginalCalculator(BayesIm, Evidence) - Constructor for class edu.cmu.tetrad.bayes.CptInvariantMarginalCalculator
Constructs a new marginal calculator for the given updated Bayes IM.
CptInvariantUpdater - Class in edu.cmu.tetrad.bayes
Calculates updated probabilities for variables conditional on their parents as well as single-variable updated marginals for a Bayes IM using an algorithm that restricts expensive updating summations only to conditional probabilities of variables with respect to their parents that change from non-updated to updated values.
CptInvariantUpdater(BayesIm) - Constructor for class edu.cmu.tetrad.bayes.CptInvariantUpdater
Constructor for CptInvariantUpdater.
CptInvariantUpdater(BayesIm, Evidence) - Constructor for class edu.cmu.tetrad.bayes.CptInvariantUpdater
Constructs a new updater for the given Bayes net.
CptMap - Interface in edu.cmu.tetrad.bayes
An interface representing a map of probabilities or counts for nodes in a Bayesian network.
CptMapCounts - Class in edu.cmu.tetrad.bayes
Represents a conditional probability table (CPT) in a Bayes net.
CptMapCounts(int, int) - Constructor for class edu.cmu.tetrad.bayes.CptMapCounts
Constructs a new probability map, a map from a unique integer index for a particular node to the probability of that node taking on that value, where NaN's are not stored.
CptMapCounts(DataSet) - Constructor for class edu.cmu.tetrad.bayes.CptMapCounts
Constructs a new CptMap based on counts from a given dataset.
CptMapProbs - Class in edu.cmu.tetrad.bayes
Represents a conditional probability table (CPT) in a Bayes net.
CptMapProbs(double[][]) - Constructor for class edu.cmu.tetrad.bayes.CptMapProbs
Constructs a new probability map based on the given 2-dimensional array.
CptMapProbs(int, int) - Constructor for class edu.cmu.tetrad.bayes.CptMapProbs
Constructs a new probability map, a map from a unique integer index for a particular node to the probability of that node taking on that value, where NaN's are not stored.
CPU - Enum constant in enum class edu.cmu.tetrad.util.MillisecondTimes.Type
CPU time.
cpuTimeMillis() - Static method in class edu.cmu.tetrad.util.MillisecondTimes
cpuTimeMillis.
create(Class<? extends Algorithm>, IndependenceWrapper, ScoreWrapper) - Static method in class edu.cmu.tetrad.algcomparison.algorithm.AlgorithmFactory
Creates an algorithm.
create(Class<? extends Algorithm>, IndependenceWrapper, ScoreWrapper, Graph) - Static method in class edu.cmu.tetrad.algcomparison.algorithm.AlgorithmFactory
Creates an algorithm.
create(Class<? extends Algorithm>, Class<? extends IndependenceWrapper>, Class<? extends ScoreWrapper>) - Static method in class edu.cmu.tetrad.algcomparison.algorithm.AlgorithmFactory
Creates an algorithm.
create(Class<? extends Algorithm>, Class<? extends IndependenceWrapper>, Class<? extends ScoreWrapper>, Graph) - Static method in class edu.cmu.tetrad.algcomparison.algorithm.AlgorithmFactory
Creates an algorithm.
create(String, RandomGraph) - Static method in class edu.cmu.tetrad.algcomparison.simulation.SimulationUtils
create.
create(List<String>) - Static method in class edu.cmu.tetrad.util.ParameterUtils
Create parameters with their default values.
createCellTable(BayesIm) - Static method in class edu.cmu.tetrad.bayes.StoredCellProbs
createCellTable.
createCellTable(MlBayesIm) - Method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
createCellTable.
createCellTable(MlBayesImObs) - Method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
createCellTable.
createContinuousVariables(String[]) - Static method in class edu.cmu.tetrad.data.DataUtils
createContinuousVariables.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Creates data sets for simulation based on the given parameters and model reuse preference.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.NLSemSimulation
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Creates data sets for simulation based on the given parameters and model reuse preference.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in interface edu.cmu.tetrad.algcomparison.simulation.Simulation
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.SingleDatasetSimulation
Creates a new data model for the simulation.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs
Creates a data set and simulates data.
createData(Parameters, boolean) - Method in class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
Creates a data set and simulates data.
createDataSamples(DataSet, Parameters) - Static method in class edu.cmu.tetrad.data.DataSampling
Create a list of dataset resampled from the given dataset.
createDataSamples(DataSet, Parameters, RandomGenerator) - Static method in class edu.cmu.tetrad.data.DataSampling
Create a list of dataset resampled from the given dataset.
createDisplayGraph(Graph, ResamplingEdgeEnsemble) - Static method in class edu.cmu.tetrad.util.GraphSampling
Create a graph for displaying and print out.
createExpression(Expression...) - Method in interface edu.cmu.tetrad.calculator.expression.ExpressionDescriptor
Creates the actual expression that can be used to evaluate matters from the given expressions.
createGraph(Parameters) - Method in class edu.cmu.tetrad.algcomparison.graph.Cyclic
createGraph.
createGraph(Parameters) - Method in class edu.cmu.tetrad.algcomparison.graph.ErdosRenyi
createGraph.
createGraph(Parameters) - Method in class edu.cmu.tetrad.algcomparison.graph.RandomForward
Creates a random graph by adding forward edges.
createGraph(Parameters) - Method in interface edu.cmu.tetrad.algcomparison.graph.RandomGraph
createGraph.
createGraph(Parameters) - Method in class edu.cmu.tetrad.algcomparison.graph.RandomSingleFactorMim
createGraph.
createGraph(Parameters) - Method in class edu.cmu.tetrad.algcomparison.graph.RandomTwoFactorMim
createGraph.
createGraph(Parameters) - Method in class edu.cmu.tetrad.algcomparison.graph.ScaleFree
createGraph.
createGraph(Parameters) - Method in class edu.cmu.tetrad.algcomparison.graph.SingleGraph
createGraph.
createGraphWithHighProbabilityEdges(List<Graph>) - Static method in class edu.cmu.tetrad.util.GraphSampling
Combine all the edges from the list of graphs onto one graph with the edge type that has the highest frequency probability.
createGraphWithHighProbabilityEdges(List<Graph>, ResamplingEdgeEnsemble) - Static method in class edu.cmu.tetrad.util.GraphSampling
createGraphWithHighProbabilityEdges.
createGraphWithoutNullEdges(Graph) - Static method in class edu.cmu.tetrad.util.GraphSampling
Create a graph from the given graph that contains no null edges.
createLagData(DataSet, int) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
Creates new time series dataset from the given one (fixed to deal with mixed datasets)
createRandomCellTable() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
createRandomCellTable.
createRandomCellTable(List<Node>) - Static method in class edu.cmu.tetrad.bayes.StoredCellProbs
createRandomCellTable.
createShiftedData(DataSet, int[]) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
createShiftedData.
crossTab(int, int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealEvaluator
This method computes the cross tablulation (table) of values of a gene and its possible parent.
crossTab(int, int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealEvaluator
This method computes the cross tablulation (table) of values of a gene and its possible parent.
crossTabulation() - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Computes the "confusion matrix" of coefs of the number of cases associated with each combination of estimated and observed values in the test dataset.
crossTabulation() - Method in interface edu.cmu.tetrad.classify.ClassifierDiscrete
crossTabulation.
crossTabulation() - Method in class edu.cmu.tetrad.classify.ClassifierMbDiscrete
crossTabulation.
cStar(LinkedList<LinkedList<Cstar.Record>>) - Static method in class edu.cmu.tetrad.search.Cstar
Returns a list of records for making a CSTaR table.
Cstar - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
Cstar class.
Cstar - Class in edu.cmu.tetrad.search
Implements the CStaR algorithm (Stekhoven et al., 2012), which finds a CPDAG of that data and then tries all orientations of the undirected edges about a variable in the CPDAG to estimate a minimum bound on the effect for a given edge.
Cstar() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Constructor for Cstar.
Cstar(IndependenceWrapper, ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Constructor for Cstar.
Cstar(IndependenceWrapper, ScoreWrapper, Parameters) - Constructor for class edu.cmu.tetrad.search.Cstar
Constructor.
CSTAR_CPDAG_ALGORITHM - Static variable in class edu.cmu.tetrad.util.Params
Constant CSTAR_CPDAG_ALGORITHM="cstarCpdagAlgorithm"
Cstar.CpdagAlgorithm - Enum Class in edu.cmu.tetrad.search
An enumeration of the options available for determining the CPDAG used for the algorithm.
Cstar.Record - Class in edu.cmu.tetrad.search
Represents a single record in the returned table for CSTaR.
Cstar.SampleStyle - Enum Class in edu.cmu.tetrad.search
An enumeration of the methods for selecting samples from the full dataset.
cu(double[], double[], double[]) - Static method in class edu.cmu.tetrad.search.Fask
Calculates the expected correlation between two arrays of double values where the condition is greater than 0.
cumulativeProbability(double) - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Calculates the cumulative probability of a given point.
cumulativeProbability(double, double) - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Deprecated.
This method is deprecated and will be removed in a future release.
currentRepositoryVersion() - Static method in class edu.cmu.tetrad.util.Version
currentRepositoryVersion.
currentViewableVersion() - Static method in class edu.cmu.tetrad.util.Version
currentViewableVersion.
CUTOFF_CONSTRAIN_SEARCH - Static variable in class edu.cmu.tetrad.util.Params
Constant CUTOFF_CONSTRAIN_SEARCH="cutoffConstrainSearch"
CUTOFF_DATA_SEARCH - Static variable in class edu.cmu.tetrad.util.Params
Constant CUTOFF_DATA_SEARCH="cutoffDataSearch"
CUTOFF_IND_TEST - Static variable in class edu.cmu.tetrad.util.Params
Constant CUTOFF_IND_TEST="cutoffIndTest"
CutoffFinder - Class in edu.cmu.tetrad.util
Provides a static method for finding the cutoff value for a symmetric probability distribution function about the origin.
Cyclic - Class in edu.cmu.tetrad.algcomparison.graph
Returns a cyclic graph build up from small cyclic graph components.
Cyclic() - Constructor for class edu.cmu.tetrad.algcomparison.graph.Cyclic
Initializes a new instance of the Cyclic class.
CYCLIC_CONSTRUCTED_FROM_SMALL_LOOPS - Static variable in class edu.cmu.tetrad.algcomparison.graph.GraphTypes
Constant CYCLIC_CONSTRUCTED_FROM_SMALL_LOOPS="Cyclic (Constructed From Small Loops)"

D

D() - Method in record class edu.cmu.tetrad.search.test.Kci.EigenReturn
Returns the value of the D record component.
Dag - Class in edu.cmu.tetrad.graph
Represents a directed acyclic graph--that is, a graph containing only directed edges, with no cycles.
Dag() - Constructor for class edu.cmu.tetrad.graph.Dag
Constructs a new directed acyclic graph (DAG).
Dag(Graph) - Constructor for class edu.cmu.tetrad.graph.Dag
Constructs a new directed acyclic graph from the given graph object.
Dag(List<Node>) - Constructor for class edu.cmu.tetrad.graph.Dag
Constructor for Dag.
dagFromCpdag(Graph) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Converts a completed partially directed acyclic graph (CPDAG) into a directed acyclic graph (DAG).
dagFromCpdag(Graph, boolean) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Converts a completed partially directed acyclic graph (CPDAG) into a directed acyclic graph (DAG).
dagFromCpdag(Graph, boolean, boolean) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Converts a completed partially directed acyclic graph (CPDAG) into a directed acyclic graph (DAG).
dagFromCpdag(Graph, Knowledge) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
dagFromCpdag.
dagFromCpdag(Graph, Knowledge, boolean, boolean) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Returns a random DAG from the given CPDAG.
DagInCpcagIterator - Class in edu.cmu.tetrad.search.utils
Given a CPDAG, lists all the DAGs in that DPCAG.
DagInCpcagIterator(Graph) - Constructor for class edu.cmu.tetrad.search.utils.DagInCpcagIterator
The given CPDAG must be a CPDAG.
DagInCpcagIterator(Graph, Knowledge) - Constructor for class edu.cmu.tetrad.search.utils.DagInCpcagIterator
The given CPDAG must be a CPDAG.
DagInCpcagIterator(Graph, Knowledge, boolean, boolean) - Constructor for class edu.cmu.tetrad.search.utils.DagInCpcagIterator
The given CPDAG must be a CPDAG.
DagIterator - Class in edu.cmu.tetrad.search.utils
Given a graph, lists all DAGs that result from directing the undirected edges in that graph every possible way.
DagIterator(Graph) - Constructor for class edu.cmu.tetrad.search.utils.DagIterator
The given CPDAG must be a CPDAG.
Dagma - Class in edu.cmu.tetrad.algcomparison.algorithm.continuous.dag
Implements the DAGMA algorithm.
Dagma - Class in edu.cmu.tetrad.search
Implements the DAGMA algorithm.
Dagma() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Dagma
Constructor for Dagma.
Dagma(DataSet) - Constructor for class edu.cmu.tetrad.search.Dagma
Constructor.
DagScorer - Class in edu.cmu.tetrad.sem
Estimates a SemIm given a CovarianceMatrix and a SemPm.
DagScorer - Interface in edu.cmu.tetrad.search.utils
Interface for a method that scores a DAG.
DagScorer(DataSet) - Constructor for class edu.cmu.tetrad.sem.DagScorer
Constructs a new SemEstimator that uses the specified optimizer.
DagScorer(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.sem.DagScorer
Constructs a new SemEstimator that uses the specified optimizer.
DagSepsets - Class in edu.cmu.tetrad.search.utils
Determines sepsets, collider, and noncolliders by examining d-separation facts in a DAG.
DagSepsets(Graph) - Constructor for class edu.cmu.tetrad.search.utils.DagSepsets
Constructs a new DagSepsets object for the given DAG.
dagToCpdag(Graph) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Returns the completed partially directed acyclic graph (CPDAG) for a given directed acyclic graph (DAG).
dagToMag(Graph) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Converts a Directed Acyclic Graph (DAG) to a Maximal Ancestral Graph (MAG) by adding arrows to the edges.
dagToPag(Graph) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Converts a Directed Acyclic Graph (DAG) to a Partial Ancestral Graph (PAG) using the DagToPag algorithm.
DagToPag - Class in edu.cmu.tetrad.search.utils
Converts a DAG (Directed acyclic graph) into the PAG (partial ancestral graph) which it is in the equivalence class of.
DagToPag(Graph) - Constructor for class edu.cmu.tetrad.search.utils.DagToPag
Constructs a new FCI search for the given independence test and background knowledge.
DATA_TYPE - Static variable in class edu.cmu.tetrad.util.Params
Constant DATA_TYPE="dataType"
DataBox - Interface in edu.cmu.tetrad.data
Stores a 2D array of data.
DataConvertUtils - Class in edu.cmu.tetrad.util
Dec 15, 2018 11:10:30 AM
DataFilter - Interface in edu.cmu.tetrad.data
Interface implemented by classes whose purpose is to generate modifications of data sets.
DataForCalibrationRfci - Class in edu.cmu.tetrad.calibration
DataForCalibrationRfci class.
DataGraphSearch - Class in edu.pitt.csb.stability
Created by ajsedgewick on 9/4/15.
DataGraphSearch(double...) - Constructor for class edu.pitt.csb.stability.DataGraphSearch
Constructor for DataGraphSearch.
DataGraphUtils - Class in edu.cmu.tetrad.data
Sundry graph utils that need to be located in the data package to avoid package cycles.
DataModel - Interface in edu.cmu.tetrad.data
Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataModelList - Class in edu.cmu.tetrad.data
Stores a list of data models and keeps track of which one is selected.
DataModelList() - Constructor for class edu.cmu.tetrad.data.DataModelList
Constructor for DataModelList.
DataModelList(DataModelList) - Constructor for class edu.cmu.tetrad.data.DataModelList
Constructor for DataModelList.
DataSampling - Class in edu.cmu.tetrad.data
A utility for resampling dataset.
DataSet - Interface in edu.cmu.tetrad.data
Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
DataSetProbs - Class in edu.cmu.tetrad.bayes
Estimates maximum likelihood probabilities directly from data on the fly.
DataSetProbs(DataSet) - Constructor for class edu.cmu.tetrad.bayes.DataSetProbs
Creates a cell count table for the given data set.
DataTable<N,V> - Interface in edu.pitt.isp.sverchkov.data
Data table implementation.
dataTableFromFile(File) - Static method in class edu.pitt.isp.sverchkov.data.DataTools
Reads a data table from a file.
DataTableImpl<N,V> - Class in edu.pitt.isp.sverchkov.data
Data table implementation.
DataTableImpl(List<? extends N>) - Constructor for class edu.pitt.isp.sverchkov.data.DataTableImpl
Constructor for DataTableImpl.
DataTools - Class in edu.pitt.isp.sverchkov.data
Data tools.
DataTransforms - Class in edu.cmu.tetrad.data
DataTransforms class.
dataType() - Element in annotation interface edu.cmu.tetrad.annotation.Algorithm
Description of the algorithm.
dataType() - Element in annotation interface edu.cmu.tetrad.annotation.Score
The data types that the score can be applied to.
dataType() - Element in annotation interface edu.cmu.tetrad.annotation.TestOfIndependence
Type of the test.
DataType - Enum Class in edu.cmu.tetrad.data
The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.
DataUtility - Class in edu.cmu.tetrad.util
Fast data loader for continuous or discrete data.
DataUtils - Class in edu.cmu.tetrad.data
Some static utility methods for dealing with data sets.
DataWriter - Class in edu.cmu.tetrad.data
Provides static methods for saving data to files.
Dci - Class in edu.cmu.tetrad.search.work_in_progress
Implements the DCI (Distributed Causal Inference) algorithm for learning causal structure over a set of variable from multiple datasets that each may only measure proper overlapping subsets of that sets, or datasets with some variables in common and others not.
Dci(List<IndependenceTest>) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Dci
Constructor for Dci.
Dci(List<IndependenceTest>, ResolveSepsets.Method) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Dci
Constructor for Dci.
dd - Enum constant in enum class edu.cmu.tetrad.graph.Edge.Property
Definitely direct.
decomposition() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Checks if decomposition holds, e.g., X ⊥⊥ (Y ∪ W) |Z ==> (X ⊥⊥ Y |Z) ∧ (X ⊥⊥ W |Z)
deepCopy(DataSet) - Static method in class edu.pitt.csb.mgm.MixedUtils
Makes a deep copy of a dataset (Nodes copied as well).
defaultCategory(int) - Static method in class edu.cmu.tetrad.data.DataUtils
defaultCategory.
defaultConfiguration(Graph, Knowledge) - Static method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Returns a default configuration of the FciOrientDataExaminationStrategy object.
defaultConfiguration(IndependenceTest, Knowledge) - Static method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Returns a default configuration of the FciOrientDataExaminationStrategy object.
defaultConfiguration(TeyssierScorer, Knowledge, boolean) - Static method in class edu.cmu.tetrad.search.utils.R0R4StrategyScoreBased
Returns a default configuration of the FciOrientDataExaminationStrategy.
DefaultEvent(String, String) - Constructor for class edu.cmu.tetrad.util.DefaultTetradLoggerConfig.DefaultEvent
Constructs the event.
defaultLayout(Graph) - Static method in class edu.cmu.tetrad.graph.LayoutUtil
Arranges the nodes in the graph in a circle if there are 20 or fewer nodes, otherwise arranges them in a square.
DefaultSetEndpointStrategy - Class in edu.cmu.tetrad.search.utils
The DefaultSetEndpointStrategy class implements the SetEndpointStrategy interface and provides a default strategy for setting the endpoint of an edge in a graph.
DefaultSetEndpointStrategy() - Constructor for class edu.cmu.tetrad.search.utils.DefaultSetEndpointStrategy
Creates a new instance of DefaultSetEndpointStrategy.
DefaultTetradLoggerConfig - Class in edu.cmu.tetrad.util
Logger configuration.
DefaultTetradLoggerConfig(String...) - Constructor for class edu.cmu.tetrad.util.DefaultTetradLoggerConfig
Constructs the config for the given event ids.
DefaultTetradLoggerConfig(List<TetradLoggerConfig.Event>) - Constructor for class edu.cmu.tetrad.util.DefaultTetradLoggerConfig
Constructs the config given the events in it.
DefaultTetradLoggerConfig.DefaultEvent - Class in edu.cmu.tetrad.util
A default implementation of the event.
DefiniteDirectedPathPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
DefiniteDirectedPathPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathPrecision
Initializes a new instance of the DefiniteDirectedPathPrecision class.
DefiniteDirectedPathRecall - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
DefiniteDirectedPathRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathRecall
Initializes a new instance of the DefiniteDirectedPathRecall class.
definiteNonDescendent(Node, Node) - Method in class edu.cmu.tetrad.graph.Paths
added by ekorber, 2004/06/12
DEFLATION - Static variable in class edu.cmu.tetrad.search.FastIca
The algorithm type where the components are extracted one at a time.
defVisible(Edge) - Method in class edu.cmu.tetrad.graph.Paths
Returns true just in case the given edge is definitely visible.
DegenerateGaussianBicScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for degenerate Gaussian BIC score
DegenerateGaussianBicScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.DegenerateGaussianBicScore
Initializes a new instance of the DegenerateGaussianBicScore class.
DegenerateGaussianLRT - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for DG LRT.
DegenerateGaussianLRT() - Constructor for class edu.cmu.tetrad.algcomparison.independence.DegenerateGaussianLRT
Initializes a new instance of the DegenerateGaussianLRT class.
DegenerateGaussianScore - Class in edu.cmu.tetrad.search.score
=This implements the degenerate Gaussian BIC score for FGES.
DegenerateGaussianScore(DataSet, boolean) - Constructor for class edu.cmu.tetrad.search.score.DegenerateGaussianScore
Constructs the score using a dataset.
degree(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Calculates the maximum degree of a graph.
DELIMITER - Static variable in class edu.pitt.isp.sverchkov.data.DataTools
Constant DELIMITER=", "
DELIMITER_REGEX - Static variable in class edu.pitt.isp.sverchkov.data.DataTools
Constant DELIMITER_REGEX=" *, *"
DelimiterType - Class in edu.cmu.tetrad.data
Type-safe enum of delimiter types for parsing data.
DelimiterUtils - Class in edu.cmu.tetrad.util
Jun 20, 2017 12:09:05 PM
DeltaSextadTest - Class in edu.cmu.tetrad.search.utils
Implements a test for simultaneously zero sextads in the style of Bollen, K.
DeltaSextadTest(DataSet) - Constructor for class edu.cmu.tetrad.search.utils.DeltaSextadTest
Constructs a test using a given data set.
DeltaSextadTest(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.search.utils.DeltaSextadTest
Constructs a test using the given covariance matrix.
DeltaTetradTest - Class in edu.cmu.tetrad.search.utils
Implements a test for simultaneously zero tetrads in Bollen, K.
DeltaTetradTest(DataSet) - Constructor for class edu.cmu.tetrad.search.utils.DeltaTetradTest
Constructs a test using a given data set.
DeltaTetradTest(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.search.utils.DeltaTetradTest
Constructs a test using the given covariance matrix.
demean(double[][], Vector) - Static method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
demean.
demix() - Method in class edu.cmu.tetrad.search.work_in_progress.Demixer
Runs the E-M algorithm iteratively until the weights array converges.
Demixer - Class in edu.cmu.tetrad.search.work_in_progress
Uses expectation-maximization to sort a a data set with data sampled from two or more multivariate Gaussian distributions into its component data sets.
Demixer(DataSet, int) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Demixer
Constructor.
DemixerMMLKun - Class in edu.cmu.tetrad.search.work_in_progress
Created by user on 2/27/18.
DemixerMMLKun() - Constructor for class edu.cmu.tetrad.search.work_in_progress.DemixerMMLKun
Constructor for DemixerMMLKun.
density(double) - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Calculates the probability density function (PDF) of a given point.
DensityEst - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
DensityEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.DensityEst
Initializes a new instance of the DensityEst class.
DensityTrue - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
DensityTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.DensityTrue
Initializes a new instance of the DensityTrue class.
dependenceFactMsg(Node, Node, Set<Node>, double) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
dependenceFactMsg.
dependent - Enum constant in enum class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCInference.OP
The operation is dependent.
DEPENDENT - Enum constant in enum class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCCausalInference.OP
The operation is dependent.
depth - Variable in class edu.cmu.tetrad.calibration.DataForCalibrationRfci
Constant depth=5
DEPTH - Static variable in class edu.cmu.tetrad.util.Params
Constant DEPTH="depth"
description() - Element in annotation interface edu.cmu.tetrad.annotation.Score
The description of the score.
description() - Element in annotation interface edu.cmu.tetrad.annotation.TestOfIndependence
Description of the test.
deserializeArchivedVersions() - Method in class edu.cmu.tetrad.util.TetradSerializableUtils
Deserializes examplars stored in archives in getArchiveDirectory().
deserializeCurrentDirectory() - Method in class edu.cmu.tetrad.util.TetradSerializableUtils
Deserializes all files in the given directory, as a test to make sure they can all be deserialized.
det() - Method in class edu.cmu.tetrad.util.Matrix
det.
determinant(double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
determinant.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.IndTestIod
Determines whether the variables in z determine x.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.score.BdeuScore
Determines whether a set of nodes z determines a specific node y.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.score.EbicScore
Returns true iff the score determines the edge between x and y.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.score.GicScores
Returns true iff the score determines the edge between x and y.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.score.ImagesScore
Returns true iff the score determines the edge between x and y.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.score.IndTestScore
Returns true iff the score determines the edge between x and y.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.score.MvpScore
Returns true iff the score determines the edge between x and y.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.score.PoissonPriorScore
Returns true iff the score determines the edge between x and y.
determines(List<Node>, Node) - Method in interface edu.cmu.tetrad.search.score.Score
Returns true iff the score determines the edge between x and y.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns true is the variables in z determine the variable y.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.score.ZsbScore
Returns true iff the score determines the edge between x and y.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Determines whether variable x is independent of variable y given a list of conditioning nodes.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Determines whether a given list of nodes (z) determines a node (y).
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Determines if a given Node x is determined by a list of Nodes z.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
Determines whether the z nodes determine the x node.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Determines if a given list of conditioning nodes (z) determines the value of a specific node (x).
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Determines whether variable x is independent of variable y given a list of conditioning variables z.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
Determines if the given list of nodes (z) determines the specified node (y).
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestMulti
Determines whether variable x is independent of variable y given a list of conditioning variables z.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestMvpLrt
Determines whether two nodes are independent given a set of conditioning nodes.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestRegression
Determines if a variable xVar can be determined by a list of conditioning variables zList.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Determines the independence between a set of variables z and a variable x.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.MsepTest
Determines if a node is m-separated from a set of conditioning nodes.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Determines the result of an independence test between a set of variables and a target variable.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Determines whether the given variables are conditionally independent.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
Determines if a given set of nodes z determines the node y.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMnlrLr
Determines the independence relation between a list of conditioning nodes and a target node.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
Determines if Node y is determined by the given list of Nodes z.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Determines if there exists a causal relationship between the nodes in z and node x.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
Determines if a given Node is present in a List of Nodes.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Determines whether a given node y is determined by a list of nodes z.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Determines if the given list of nodes can determine the specified node.
determines(List<Node>, Node) - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Determines whether the given list of nodes has a specific relationship with the specified node.
determines(List<Node>, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Returns true iff the score determines the edge between x and y.
determines(List<Node>, Node) - Method in class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
Determines the independence between a set of variables and a target variable.
determines(List, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Determines the independence between a list of conditioning variables (z) and a target variable (x).
determines(Set<Node>, Node) - Method in interface edu.cmu.tetrad.search.IndependenceTest
Returns true if y is determined the variable in z.
determines(Set<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Determines whether variable x is independent of a set of variables _z.
determines(Set<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Determines whether variable x is independent of a set of variables _z.
determines(Set<Node>, Node) - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Determines whether a given set of nodes, z, determines another node, y.
determines(Set<Node>, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Returns true if y is determined the variable in z.
determines(Set<Node>, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
Returns true if y is determined the variable in z.
DETERMINISM_THRESHOLD - Static variable in class edu.cmu.tetrad.util.Params
Constant DETERMINISM_THRESHOLD="determinismThreshold"
determinismDetected(Set<Node>, Node) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
determinismDetected.
diag() - Method in class edu.cmu.tetrad.util.Matrix
diag.
diag() - Method in class edu.cmu.tetrad.util.Vector
diag.
dieToss(int) - Static method in class edu.cmu.tetrad.util.StatUtils
dieToss.
differByPerturbation(int, int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch
This method determines whether the levels for a given gene differ between two perturbations p0 and p1 (rows of the perturbation matrix).
difference(DataSet, int) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
Calculates the dth difference of the given data.
DIFFERENT_GRAPHS - Static variable in class edu.cmu.tetrad.util.Params
Constant DIFFERENT_GRAPHS="differentGraphs"
differExpressions(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch
differExpressions.
Digraph - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua
Simple implementation of a directed Graph edges are just represented by float values (a zero == no edge) stored in a matrix.
Digraph(Digraph) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Digraph
Copy constructor.
Digraph(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Digraph
Creates a OldDigraph reading it from file fname.
Digraph(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Digraph
Creates a OldDigraph with gName name, and n nodes.
DijkstraEdge(Node, int) - Constructor for class edu.cmu.tetrad.search.FciOrientDijkstra.DijkstraEdge
Creates a new DijkstraEdge.
DijkstraEdge(Node, int) - Constructor for class edu.cmu.tetrad.search.utils.R5R9Dijkstra.DijkstraEdge
Represents an edge connecting two nodes in Dijkstra's algorithm.
directedEdge(Node, Node) - Static method in class edu.cmu.tetrad.graph.Edges
Constructs a new directed edge from nodeA to nodeB (-->).
directedPaths(Node, Node, int) - Method in class edu.cmu.tetrad.graph.Paths
Finds all directed paths from node1 to node2 with a maximum length.
DirectLingam - Class in edu.cmu.tetrad.algcomparison.algorithm.continuous.dag
Direct LiNGAM.
DirectLingam - Class in edu.cmu.tetrad.search
Implements the Direct-LiNGAM algorithm.
DirectLingam() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.DirectLingam
Constructor for DirectLingam.
DirectLingam(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.DirectLingam
Constructor for DirectLingam.
DirectLingam(DataSet, Score) - Constructor for class edu.cmu.tetrad.search.DirectLingam
Constructor.
directProduct(double[][], double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Computes the direct (Kronecker) outerProduct.
DirichletBayesIm - Class in edu.cmu.tetrad.bayes
Stores Dirichlet pseudocounts for the distributions of each variable conditional on particular combinations of its parent values and, together with Bayes Pm and Dag, provides methods to manipulate these tables.
DirichletBayesIm(DirichletBayesIm) - Constructor for class edu.cmu.tetrad.bayes.DirichletBayesIm
Copy constructor.
DirichletDataSetProbs - Class in edu.cmu.tetrad.bayes
Estimates probabilities directly from data on the fly using maximum likelihood method.
DirichletDataSetProbs(DataSet, double) - Constructor for class edu.cmu.tetrad.bayes.DirichletDataSetProbs
Creates a cell count table for the given data set.
DirichletEstimator - Class in edu.cmu.tetrad.bayes
Estimates a DirichletBayesIm from a DirichletBayesIm (the prior) and a data set.
DirichletEstimator() - Constructor for class edu.cmu.tetrad.bayes.DirichletEstimator
Creates a new instance of DirichletEstimator.
disallowComplement(int, int) - Method in class edu.cmu.tetrad.bayes.Proposition
Without changing the status of the specified category, disallows all other categories for the given variable.
Discrete - Class in edu.cmu.tetrad.util.dist
Wraps a chi square distribution for purposes of drawing random samples.
Discrete - Enum constant in enum class edu.cmu.tetrad.data.DataType
Discrete.
Discrete - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.DataType
Constant for discrete data.
DISCRETE - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
Discrete.
DISCRETE_LRT - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
Discrete LRT.
DISCRETE_VARIATIONAL - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
Discrete Variational.
DiscreteBicScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for Discrete BIC test.
DiscreteBicScore - Class in edu.cmu.tetrad.search.score
Calculates the discrete BIC score.
DiscreteBicScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.DiscreteBicScore
Initializes a new instance of the DiscreteBicScore class.
DiscreteBicScore(DataSet) - Constructor for class edu.cmu.tetrad.search.score.DiscreteBicScore
Constructs the score using a dataset.
DiscreteBicScoreAdTree - Class in edu.cmu.tetrad.search.score
Calculates the discrete BIC score.
DiscreteBicScoreAdTree(DataSet) - Constructor for class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
Constructs the score using a dataset.
DiscreteBicTest - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Fisher Z test.
DiscreteBicTest() - Constructor for class edu.cmu.tetrad.algcomparison.independence.DiscreteBicTest
Initializes a new instance of the DiscreteBicTest class.
DiscreteDiscretizationSpec - Class in edu.cmu.tetrad.data
Specifies how a column (continuous or discrete) should be discretized.
DiscreteDiscretizationSpec(int[], List<String>) - Constructor for class edu.cmu.tetrad.data.DiscreteDiscretizationSpec
Constructor for DiscreteDiscretizationSpec.
DiscreteScore - Interface in edu.cmu.tetrad.search.score
Gives an interface that can be used by various discrete scores.
discreteSerializableInstance() - Static method in class edu.cmu.tetrad.data.DataUtils
A discrete data set used to construct some other serializable instances.
DiscreteVariable - Class in edu.cmu.tetrad.data
Represents a discrete variable as a range of integer-valued categories 0, 1, ..., m - 1, where m is the number of categories for the variable.
DiscreteVariable(DiscreteVariable) - Constructor for class edu.cmu.tetrad.data.DiscreteVariable
Copy constructor.
DiscreteVariable(String) - Constructor for class edu.cmu.tetrad.data.DiscreteVariable
Builds a discrete variable with the given name and an empty list of categories.
DiscreteVariable(String, int) - Constructor for class edu.cmu.tetrad.data.DiscreteVariable
Builds a qualitative variable with the given name and number of categories.
DiscreteVariable(String, List<String>) - Constructor for class edu.cmu.tetrad.data.DiscreteVariable
Builds a qualitative variable with the given name and array of possible categories.
DiscreteVariableType - Class in edu.cmu.tetrad.data
Type-safe enum of discrete variable types.
DiscretizationSpec - Interface in edu.cmu.tetrad.data
A continuous or discrete discretization spec (see).
discretize() - Method in class edu.cmu.tetrad.data.Discretizer
discretize.
discretize(double[], double[], String, List<String>) - Static method in class edu.cmu.tetrad.data.Discretizer
Discretizes the continuous data in the given column using the specified cutoffs and category names.
discretize(DataSet, int, boolean) - Static method in class edu.cmu.tetrad.data.DataTransforms
discretize.
DISCRETIZE - Static variable in class edu.cmu.tetrad.util.Params
Constant DISCRETIZE="discretize"
Discretizer - Class in edu.cmu.tetrad.data
Discretizes individual columns of discrete or continuous data.
Discretizer(DataSet) - Constructor for class edu.cmu.tetrad.data.Discretizer
Constructs a new discretizer that discretizes every variable as binary, using evenly distributed values.
Discretizer(DataSet, Map<Node, DiscretizationSpec>) - Constructor for class edu.cmu.tetrad.data.Discretizer
Constructor for Discretizer.
Discretizer.Discretization - Class in edu.cmu.tetrad.data
A discretization specification for a continuous variable.
DiscriminatingPath - Class in edu.cmu.tetrad.search.utils
Represents a discriminating path in a graph.
DiscriminatingPath(Node, Node, Node, Node, LinkedList<Node>, boolean) - Constructor for class edu.cmu.tetrad.search.utils.DiscriminatingPath
Represents a discriminating path construct in a graph.
DishModel - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Models the manner in which gene models are initialized differentially depending on the dishes that the cells are in.
DishModel(int, double) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.DishModel
Constructor for DishModel.
display(SortedSet<ItkPredictorSearch.Gene>) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch
display.
DisplayNameHandler - Class in edu.cmu.tetrad.study.gene.tetrad.gene.graph
Translates display names of lagged variables (e.g.
displayParents() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Displays the parents.
dissimilarity(Vector, Vector) - Method in interface edu.cmu.tetrad.cluster.metrics.Dissimilarity
dissimilarity.
dissimilarity(Vector, Vector) - Method in class edu.cmu.tetrad.cluster.metrics.SquaredErrorLoss
Calculates the dissimilarity between two vectors using the Euclidean dissimilarity metric.
Dissimilarity - Interface in edu.cmu.tetrad.cluster.metrics
Interface for a dissilimarity metric.
DIST - Enum constant in enum class edu.cmu.tetrad.sem.ParamType
Represents a free parameter type for structural equation modeling (SEM) models.
distance(LinkedList<Double>, double) - Method in class edu.cmu.tetrad.search.Ida
Returns the distance between the effects and the true effect.
distances(Graph, Graph) - Method in class edu.cmu.tetrad.simulation.Gdistance
distances.
distances(FciOrientDijkstra.Graph, Node, Node, Map<Node, Node>, boolean, boolean) - Static method in class edu.cmu.tetrad.search.FciOrientDijkstra
Finds shortest distances from a x node to all other nodes in a graph.
distances(FciOrientDijkstra.Graph, Node, Map<Node, Node>) - Static method in class edu.cmu.tetrad.search.FciOrientDijkstra
Finds shortest distances from a start node to all other nodes in a graph.
distances(R5R9Dijkstra.Graph, Node, Node) - Static method in class edu.cmu.tetrad.search.utils.R5R9Dijkstra
Finds shortest distances from a x node to all other nodes in a graph, subject to the following constraints.
distinct(Node...) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Determines whether three Node objects are distinct.
Distribution - Interface in edu.cmu.tetrad.util.dist
Interface for a statistical distribution from which random values can be drawn.
district(Node) - Method in class edu.cmu.tetrad.graph.Paths
Retrieves the set of nodes that belong to the same district as the given node.
district(Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Calculates the district of a given node in a graph.
DMSearch - Class in edu.cmu.tetrad.search.work_in_progress
Implements the DM search.
DMSearch() - Constructor for class edu.cmu.tetrad.search.work_in_progress.DMSearch
Constructor for DMSearch.
DMSearch.LatentStructure - Class in edu.cmu.tetrad.search.work_in_progress
Structure to hold latent structure.
DO_COLLIDER_ORIENTATION - Static variable in class edu.cmu.tetrad.util.Params
Constant DO_COLLIDER_ORIENTATION="doColliderOrientation"
DO_DDP_EDGE_REMOVAL_STEP - Static variable in class edu.cmu.tetrad.util.Params
Constant DO_DDP_EDGE_REMOVAL_STEP="doDdpEdgeRemovalStep"
doDiscriminatingPathOrientation(DiscriminatingPath, Graph, Set<Node>) - Method in interface edu.cmu.tetrad.search.utils.R0R4Strategy
Does a discriminating path orientation based on an examination of the data.
doDiscriminatingPathOrientation(DiscriminatingPath, Graph, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyScoreBased
Does a discriminating path orientation based on the Discriminating Path Rule.
doDiscriminatingPathOrientation(DiscriminatingPath, Graph, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Does a discriminating path orientation.
dof - Variable in class edu.cmu.tetrad.bayes.BayesProperties.LikelihoodRet
The degrees of freedom.
doLayout() - Method in class edu.cmu.tetrad.graph.LayoutUtil.FruchtermanReingoldLayout
Lays out the graph.
doLayout() - Method in class edu.cmu.tetrad.graph.LayoutUtil.KamadaKawaiLayout
Lays out the graph.
DOMAIN - Enum constant in enum class edu.cmu.tetrad.graph.NodeVariableType
The node variable type not intervened on.
doRequiredOrientations(FciOrient, Graph, List<Node>, Knowledge, boolean) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Orient required edges in PAG.
dot(Vector) - Method in class edu.cmu.tetrad.util.Vector
dot.
dotProduct(Vector) - Method in class edu.cmu.tetrad.util.Vector
dotProduct.
DOUBLE_REMOVE - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move.Type
Remove two edges.
DoubleDataBox - Class in edu.cmu.tetrad.data
Stores a 2D array of double data.
DoubleDataBox(double[][]) - Constructor for class edu.cmu.tetrad.data.DoubleDataBox
Constructs a new data box using the given 2D double data array as data.
DoubleDataBox(int, int) - Constructor for class edu.cmu.tetrad.data.DoubleDataBox
Constructs an 2D double array consisting entirely of missing values (Double.NaN).
dsep(Node, Node) - Method in class edu.cmu.tetrad.graph.Paths
Returns D-SEP(x, y) for a maximal ancestral graph G (or inducing path graph G, as in Causation, Prediction and Search).
dsep(Node, Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns D-SEP(x, y) for a MAG G.
dsep0(Node, Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns D-SEP(x, y) for a MAG G (or inducing path graph G, as in Causation, Prediction and Search).
dsep2(Node, Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns D-SEP(x, y) for a MAG G.
dsepReachability(Node, Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns D-SEP(x, y) for a MAG G.

E

E - Static variable in class edu.cmu.tetrad.calculator.expression.ConstantExpression
Constant expression for e.
E(double[], double[], double[]) - Static method in class edu.cmu.tetrad.search.Fask
Calculates E(xy) for positive values of z.
E(double[], double[], double[], double, double) - Static method in class edu.cmu.tetrad.util.StatUtils
E.
Eb - Class in edu.cmu.tetrad.algcomparison.algorithm.pairwise
EB.
Eb() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Eb
Constructor for Eb.
Eb(Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Eb
Constructor for Eb.
EB - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The EB rule.
EBIC_GAMMA - Static variable in class edu.cmu.tetrad.util.Params
Constant EBIC_GAMMA="ebicGamma"
EbicScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for linear, Gaussian Extended BIC score (Chen and Chen).
EbicScore - Class in edu.cmu.tetrad.search.score
Implements the extended BIC (EBIC) score.
EbicScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.EbicScore
Initializes a new instance of the EbicScore class.
EbicScore(DataSet, boolean) - Constructor for class edu.cmu.tetrad.search.score.EbicScore
Constructs the score using a covariance matrix.
EbicScore(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.search.score.EbicScore
Constructs the score using a covariance matrix.
Edge - Class in edu.cmu.tetrad.graph
Represents an edge node1 *-# node2 where * and # are endpoints of type Endpoint--that is, Endpoint.TAIL, Endpoint.ARROW, or Endpoint.CIRCLE.
Edge(Edge) - Constructor for class edu.cmu.tetrad.graph.Edge
Constructor for Edge.
Edge(Node, Node, Endpoint, Endpoint) - Constructor for class edu.cmu.tetrad.graph.Edge
Constructs a new edge by specifying the nodes it connects and the endpoint types.
Edge.Property - Enum Class in edu.cmu.tetrad.graph
A property of an edge.
EdgeListGraph - Class in edu.cmu.tetrad.graph
Stores a graph a list of lists of edges adjacent to each node in the graph, with an additional list storing all of the edges in the graph.
EdgeListGraph() - Constructor for class edu.cmu.tetrad.graph.EdgeListGraph
Constructs a new (empty) EdgeListGraph.
EdgeListGraph(EdgeListGraph) - Constructor for class edu.cmu.tetrad.graph.EdgeListGraph
Constructor for EdgeListGraph.
EdgeListGraph(Graph) - Constructor for class edu.cmu.tetrad.graph.EdgeListGraph
Constructs a EdgeListGraph using the nodes and edges of the given graph.
EdgeListGraph(List<Node>) - Constructor for class edu.cmu.tetrad.graph.EdgeListGraph
Constructs a new graph, with no edges, using the given variable names.
edgeMisclassificationCounts(Graph, Graph, boolean) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Computes the misclassification counts for each edge in the given graphs.
edgeMisclassifications(double[][], NumberFormat) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Generates a textual representation of the edge misclassifications based on the provided counts and number format.
edgeMisclassifications(int[][]) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Calculates the misclassifications of edges based on the given counts.
edgeMisclassifications(Graph, Graph) - Static method in class edu.cmu.tetrad.graph.MisclassificationUtils
edgeMisclassifications.
edgeOrientedMsg(String, Edge) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
edgeOrientedMsg.
Edges - Class in edu.cmu.tetrad.graph
This factory class produces edges of the types commonly used for Tetrad-style graphs.
EdgeStatHeader - Static variable in class edu.pitt.csb.mgm.MixedUtils
Constant EdgeStatHeader="TD\tTU\tFL\tFD\tFU\tFPD\tFPU\tFND\tFNU\"{trunked}
EdgesToString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Digraph
Returns a string representation of the set of edges in this graph
EdgesToString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Returns a string representation of the set of edges in this graph
EdgeTypeProbability - Class in edu.cmu.tetrad.graph
Apr 13, 2017 3:56:46 PM
EdgeTypeProbability() - Constructor for class edu.cmu.tetrad.graph.EdgeTypeProbability
Constructor for EdgeTypeProbability.
EdgeTypeProbability(EdgeTypeProbability.EdgeType, double) - Constructor for class edu.cmu.tetrad.graph.EdgeTypeProbability
Constructor for EdgeTypeProbability.
EdgeTypeProbability(EdgeTypeProbability.EdgeType, List<Edge.Property>, double) - Constructor for class edu.cmu.tetrad.graph.EdgeTypeProbability
Constructor for EdgeTypeProbability.
EdgeTypeProbability.EdgeType - Enum Class in edu.cmu.tetrad.graph
An enumeration of the different types of edges.
edu.cmu.tetrad.algcomparison - package edu.cmu.tetrad.algcomparison
 
edu.cmu.tetrad.algcomparison.algorithm - package edu.cmu.tetrad.algcomparison.algorithm
 
edu.cmu.tetrad.algcomparison.algorithm.cluster - package edu.cmu.tetrad.algcomparison.algorithm.cluster
 
edu.cmu.tetrad.algcomparison.algorithm.continuous.dag - package edu.cmu.tetrad.algcomparison.algorithm.continuous.dag
 
edu.cmu.tetrad.algcomparison.algorithm.mixed - package edu.cmu.tetrad.algcomparison.algorithm.mixed
 
edu.cmu.tetrad.algcomparison.algorithm.multi - package edu.cmu.tetrad.algcomparison.algorithm.multi
 
edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag - package edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
 
edu.cmu.tetrad.algcomparison.algorithm.oracle.pag - package edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
 
edu.cmu.tetrad.algcomparison.algorithm.other - package edu.cmu.tetrad.algcomparison.algorithm.other
 
edu.cmu.tetrad.algcomparison.algorithm.pairwise - package edu.cmu.tetrad.algcomparison.algorithm.pairwise
 
edu.cmu.tetrad.algcomparison.examples - package edu.cmu.tetrad.algcomparison.examples
 
edu.cmu.tetrad.algcomparison.graph - package edu.cmu.tetrad.algcomparison.graph
 
edu.cmu.tetrad.algcomparison.independence - package edu.cmu.tetrad.algcomparison.independence
 
edu.cmu.tetrad.algcomparison.score - package edu.cmu.tetrad.algcomparison.score
 
edu.cmu.tetrad.algcomparison.simulation - package edu.cmu.tetrad.algcomparison.simulation
 
edu.cmu.tetrad.algcomparison.statistic - package edu.cmu.tetrad.algcomparison.statistic
 
edu.cmu.tetrad.algcomparison.statistic.utils - package edu.cmu.tetrad.algcomparison.statistic.utils
 
edu.cmu.tetrad.algcomparison.utils - package edu.cmu.tetrad.algcomparison.utils
 
edu.cmu.tetrad.annotation - package edu.cmu.tetrad.annotation
 
edu.cmu.tetrad.bayes - package edu.cmu.tetrad.bayes
 
edu.cmu.tetrad.calculator - package edu.cmu.tetrad.calculator
 
edu.cmu.tetrad.calculator.expression - package edu.cmu.tetrad.calculator.expression
 
edu.cmu.tetrad.calculator.parser - package edu.cmu.tetrad.calculator.parser
 
edu.cmu.tetrad.calibration - package edu.cmu.tetrad.calibration
 
edu.cmu.tetrad.classify - package edu.cmu.tetrad.classify
 
edu.cmu.tetrad.cluster - package edu.cmu.tetrad.cluster
 
edu.cmu.tetrad.cluster.metrics - package edu.cmu.tetrad.cluster.metrics
 
edu.cmu.tetrad.data - package edu.cmu.tetrad.data
 
edu.cmu.tetrad.data.simulation - package edu.cmu.tetrad.data.simulation
 
edu.cmu.tetrad.graph - package edu.cmu.tetrad.graph
 
edu.cmu.tetrad.regression - package edu.cmu.tetrad.regression
 
edu.cmu.tetrad.search - package edu.cmu.tetrad.search
Contains classes for searching for (mostly structural) causal models given data.
edu.cmu.tetrad.search.score - package edu.cmu.tetrad.search.score
Contains classes for various sorts of scores for running score-based algorithms.
edu.cmu.tetrad.search.test - package edu.cmu.tetrad.search.test
Contains classes for running conditional independence tests for various sorts of data.
edu.cmu.tetrad.search.utils - package edu.cmu.tetrad.search.utils
Contains some utility classes for search algorithms.
edu.cmu.tetrad.search.work_in_progress - package edu.cmu.tetrad.search.work_in_progress
Contains some classes that aren't ready for prime time.
edu.cmu.tetrad.sem - package edu.cmu.tetrad.sem
 
edu.cmu.tetrad.simulation - package edu.cmu.tetrad.simulation
 
edu.cmu.tetrad.stat - package edu.cmu.tetrad.stat
 
edu.cmu.tetrad.stat.correlation - package edu.cmu.tetrad.stat.correlation
 
edu.cmu.tetrad.study - package edu.cmu.tetrad.study
 
edu.cmu.tetrad.study.examples.conditions - package edu.cmu.tetrad.study.examples.conditions
 
edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu - package edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu
 
edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua - package edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua
 
edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker - package edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker
 
edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal - package edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal
 
edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin - package edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
 
edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util - package edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util
 
edu.cmu.tetrad.study.gene.tetrad.gene.graph - package edu.cmu.tetrad.study.gene.tetrad.gene.graph
Contains an editable display graph for (small) lag graphs.
edu.cmu.tetrad.study.gene.tetrad.gene.history - package edu.cmu.tetrad.study.gene.tetrad.gene.history
Implements a time-series simulation engine suitable for time-series gene expression studies.
edu.cmu.tetrad.study.gene.tetrad.gene.simexp - package edu.cmu.tetrad.study.gene.tetrad.gene.simexp
Implements a collection of manual simulation experiments.
edu.cmu.tetrad.study.gene.tetrad.gene.simulation - package edu.cmu.tetrad.study.gene.tetrad.gene.simulation
Contains classes for generating simulations of expression levels over a collection of genes.
edu.cmu.tetrad.study.gene.tetrad.gene.util - package edu.cmu.tetrad.study.gene.tetrad.gene.util
Contains some utility classes needed for the edu.cmu.tetrad.gene.* packages.
edu.cmu.tetrad.study.gene.tetradapp.model - package edu.cmu.tetrad.study.gene.tetradapp.model
 
edu.cmu.tetrad.study.performance - package edu.cmu.tetrad.study.performance
 
edu.cmu.tetrad.util - package edu.cmu.tetrad.util
 
edu.cmu.tetrad.util.dist - package edu.cmu.tetrad.util.dist
 
edu.pitt.csb.mgm - package edu.pitt.csb.mgm
 
edu.pitt.csb.stability - package edu.pitt.csb.stability
 
edu.pitt.dbmi.algo.bayesian.constraint.inference - package edu.pitt.dbmi.algo.bayesian.constraint.inference
 
edu.pitt.dbmi.algo.bayesian.constraint.search - package edu.pitt.dbmi.algo.bayesian.constraint.search
 
edu.pitt.dbmi.algo.resampling - package edu.pitt.dbmi.algo.resampling
 
edu.pitt.isp.sverchkov.data - package edu.pitt.isp.sverchkov.data
 
EffectiveSampleSizeSettable - Interface in edu.cmu.tetrad.search
Gives an interface for classes where the effective sample size can be set by the user.
EigenDecomposition - Class in edu.pitt.csb.mgm
Calculates the eigen decomposition of a real matrix.
EigenDecomposition(double[], double[]) - Constructor for class edu.pitt.csb.mgm.EigenDecomposition
Calculates the eigen decomposition of the symmetric tridiagonal matrix.
EigenDecomposition(double[], double[], double) - Constructor for class edu.pitt.csb.mgm.EigenDecomposition
Deprecated.
in 3.1 (to be removed in 4.0) due to unused parameter
EigenDecomposition(RealMatrix) - Constructor for class edu.pitt.csb.mgm.EigenDecomposition
Calculates the eigen decomposition of the given real matrix.
EigenDecomposition(RealMatrix, double) - Constructor for class edu.pitt.csb.mgm.EigenDecomposition
Deprecated.
in 3.1 (to be removed in 4.0) due to unused parameter
EigenReturn(SimpleMatrix, SimpleMatrix, List<Double>) - Constructor for record class edu.cmu.tetrad.search.test.Kci.EigenReturn
Creates an instance of a EigenReturn record class.
Elapsed - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The elapsed time.
Elapsed - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant Elapsed
ElapsedCpuTime - Class in edu.cmu.tetrad.algcomparison.statistic
Records the elapsed time of the algorithm in seconds.
ElapsedCpuTime() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ElapsedCpuTime
Initializes a new instance of the ElapsedCpuTime class.
EmBayesEstimator - Class in edu.cmu.tetrad.bayes
Estimates parameters of the given Bayes net from the given data using maximum likelihood method.
EmBayesEstimator(BayesIm, DataSet) - Constructor for class edu.cmu.tetrad.bayes.EmBayesEstimator
Constructor for EmBayesEstimator.
EmBayesEstimator(BayesPm, DataSet) - Constructor for class edu.cmu.tetrad.bayes.EmBayesEstimator
Provides methods for estimating a Bayes IM from an existing BayesIM and a discrete dataset using EM (Expectation Maximization).
EmBayesProperties - Class in edu.cmu.tetrad.bayes
Calculates some scores for Bayes nets as a whole.
EmBayesProperties(DataSet, Graph) - Constructor for class edu.cmu.tetrad.bayes.EmBayesProperties
Constructor for EmBayesProperties.
EmBayesProperties.Estimator - Interface in edu.cmu.tetrad.bayes
Interface for an estimator.
EmpiricalCdf - Class in edu.cmu.tetrad.sem
Only the cumulativeProbability, density, setShift methods are implemented.
EmpiricalCdf(List<Double>) - Constructor for class edu.cmu.tetrad.sem.EmpiricalCdf
Constructor for EmpiricalCdf.
EmpiricalDistributionForExpression - Class in edu.cmu.tetrad.sem
Returns a sample empirical distribution for a particular expression.
EmpiricalDistributionForExpression(GeneralizedSemPm, Node, Context) - Constructor for class edu.cmu.tetrad.sem.EmpiricalDistributionForExpression
Constructor for EmpiricalDistributionForExpression.
empiricalHSIC(Matrix, Matrix, int) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Empirical unconditional Hilbert-Schmidt Dependence Measure for X and Y
empiricalHSICincompleteCholesky(Matrix, Matrix, int) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Empirical unconditional Hilbert-Schmidt Dependence Measure for X and Y using incomplete Cholesky decomposition to approximate Gram matrices
empiricalHSICincompleteCholesky(Matrix, Matrix, Matrix, int) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Empirical unconditional Hilbert-Schmidt Dependence Measure for X and Y given Z using incomplete Cholesky decomposition to approximate Gram matrices
EmptyConfig(boolean) - Constructor for class edu.cmu.tetrad.util.TetradLogger.EmptyConfig
Constructor for EmptyConfig.
emptyGraph(int) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Creates an empty graph with the specified number of nodes.
Endpoint - Enum Class in edu.cmu.tetrad.graph
A enumeration of the endpoint types that are permitted in Tetrad-style graphs: null (-), arrow (->), circle (-o), start (-*), and null (no endpoint).
endpointMisclassification(Graph, Graph) - Static method in class edu.cmu.tetrad.graph.MisclassificationUtils
endpointMisclassification.
endpointMisclassification(List<Node>, Graph, Graph) - Static method in class edu.cmu.tetrad.study.performance.PerformanceTests
endpointMisclassification.
ENSURE_MARKOV - Static variable in class edu.cmu.tetrad.util.Params
Constant ENSURE_MARKOV="ensureMarkov"
ensureColumns(int, List<String>) - Method in class edu.cmu.tetrad.data.BoxDataSet
Ensures that the dataset has at least columns columns.
ensureColumns(int, List<String>) - Method in interface edu.cmu.tetrad.data.DataSet
Ensures that the dataset has at least columns columns.
ensureColumns(int, List<String>) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Ensures that the dataset has at least columns columns.
EnsureMarkov - Class in edu.cmu.tetrad.search.utils
A helper class to encapsulate logic for ensuring a Markov property for subsequent testing after an initial local Markov graph has been found.
EnsureMarkov(Graph, IndependenceTest) - Constructor for class edu.cmu.tetrad.search.utils.EnsureMarkov
Constructs an EnsureMarkov class for a given Markov dag.
ensureRows(int) - Method in class edu.cmu.tetrad.data.BoxDataSet
Ensures that the dataset has at least rows rows.
ensureRows(int) - Method in interface edu.cmu.tetrad.data.DataSet
Ensures that the dataset has at least rows rows.
ensureRows(int) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Ensures that the dataset has at least rows rows.
ensureSymmetry() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Sets symmetry as assumed--i.e., ensures that X ⊥⊥ Y | Z ==> Y ⊥⊥ X | Z.
ensureTriviality() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Sets whether triviality as assumed.
entropy - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Score
The entropy.
entropy(int[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealEvaluator
This method computes the entropy of a binary signal stored in an int array.
entropy(int[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.LTestReveal
entropy.
entropy(int[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealEvaluator
This method computes the entropy of a binary signal stored in an int array.
entropy(int, double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
entropy.
entropy(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealEvaluator
This method implements the same definition of entropy as above but this specialized version is intended to be used by the mutualInformation method (viz).
entropy(int, int) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.LTestReveal
entropy.
entropy(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealEvaluator
This method implements the same definition of entropy as above but this specialized version is intended to be used by the mutualInformation method (viz).
EOF - Enum constant in enum class edu.cmu.tetrad.calculator.parser.Token
End of file.
EQ - Enum constant in enum class edu.cmu.tetrad.sem.ParamComparison
An enum representing the "EQ" comparison type for a parameter in SEM estimation.
EQ - Enum constant in enum class edu.cmu.tetrad.sem.ParamConstraintType
The EQ represents a parameter constraint type EQ (equal).
equalCounts(Node, int) - Method in class edu.cmu.tetrad.data.Discretizer
Sets the given node to discretized using evenly distributed values using the given number of categories.
equalIntervals(Node, int) - Method in class edu.cmu.tetrad.data.Discretizer
Sets the given node to discretized using evenly spaced intervals using the given number of categories.
equals(double[][], double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Tests two matrices for equality.
equals(double[][], double[][], double) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Tests to see whether two matrices are equal within the given tolerance.
equals(double[], double[]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Tests two vectors for equality.
equals(double[], double[], double) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Tests to see whether two vectors are equal within the given tolerance.
equals(ScoredGraph) - Method in class edu.cmu.tetrad.search.score.ScoredGraph
Returns true if the scoreed graph and this scored graph are equal.
equals(Matrix, double) - Method in class edu.cmu.tetrad.util.Matrix
equals.
equals(Object) - Method in class edu.cmu.tetrad.annotation.AnnotatedClass
 
equals(Object) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns true iff this Bayes net is equal to the given Bayes net.
equals(Object) - Method in class edu.cmu.tetrad.bayes.BayesPm
equals(Object) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns true iff this Bayes net is equal to the given Bayes net.
equals(Object) - Method in class edu.cmu.tetrad.bayes.Evidence
equals(Object) - Method in class edu.cmu.tetrad.bayes.Manipulation
equals(Object) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Determines whether the specified object is equal to this Bayes net.
equals(Object) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns true iff this Bayes net is equal to the given Bayes net.
equals(Object) - Method in class edu.cmu.tetrad.bayes.Proposition
equals(Object) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns true iff this Bayes net is equal to the given Bayes net.
equals(Object) - Method in class edu.cmu.tetrad.data.BoxDataSet
Checks if the given object is equal to this dataset.
equals(Object) - Method in class edu.cmu.tetrad.data.Clusters
equals(Object) - Method in class edu.cmu.tetrad.data.ContinuousVariable
Tests whether this variable is equal to the given variable.
equals(Object) - Method in class edu.cmu.tetrad.data.DataModelList
equals(Object) - Method in interface edu.cmu.tetrad.data.DataSet
Checks if the given object is equal to this dataset.
equals(Object) - Method in class edu.cmu.tetrad.data.DiscreteVariable
Tests whether this variable is equal to the given variable.
equals(Object) - Method in class edu.cmu.tetrad.data.Knowledge
Compares this Knowledge object with the specified object for equality.
equals(Object) - Method in class edu.cmu.tetrad.data.KnowledgeEdge
equals(Object) - Method in class edu.cmu.tetrad.data.KnowledgeGroup
equals(Object) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Checks if the given object is equal to this dataset.
equals(Object) - Method in class edu.cmu.tetrad.graph.Dag
Compares this Graph object with the specified object for equality.
equals(Object) - Method in class edu.cmu.tetrad.graph.Edge
equals(Object) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Determines whether this graph is equal to some other graph, in the sense that they contain the same nodes and the sets of edges defined over these nodes in the two graphs are isomorphic typewise.
equals(Object) - Method in interface edu.cmu.tetrad.graph.Graph
Determines whether this graph is equal to some other graph, in the sense that they contain the same nodes and the sets of edges defined over these nodes in the two graphs are isomorphic typewise.
equals(Object) - Method in class edu.cmu.tetrad.graph.GraphNode
Tests whether this variable is equal to the given variable.
equals(Object) - Method in class edu.cmu.tetrad.graph.IndependenceFact
equals(Object) - Method in interface edu.cmu.tetrad.graph.Node
Tests whether this variable is equal to the given variable.
equals(Object) - Method in class edu.cmu.tetrad.graph.NodePair
equals(Object) - Method in class edu.cmu.tetrad.graph.OrderedPair
equals(Object) - Method in class edu.cmu.tetrad.graph.SemGraph
Determines whether this graph is equal to some other graph, in the sense that they contain the same nodes and the sets of edges defined over these nodes in the two graphs are isomorphic typewise.
equals(Object) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Compares this Graph object with the specified object for equality.
equals(Object) - Method in class edu.cmu.tetrad.graph.Triple
equals(Object) - Method in record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class edu.cmu.tetrad.search.score.SemBicScore.CovAndCoefs
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in record class edu.cmu.tetrad.search.test.Kci.EigenReturn
Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms.GraphoidIndFact
Returns whether this object is equal to another.
equals(Object) - Method in class edu.cmu.tetrad.search.utils.PossibleMConnectingPath
equals(Object) - Method in class edu.cmu.tetrad.search.utils.SepsetMap
equals(Object) - Method in class edu.cmu.tetrad.search.utils.Sextad
equals(Object) - Method in class edu.cmu.tetrad.search.utils.Tetrad
equals(Object) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
equals(Object) - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
equals(Object) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.GraphWithPValue
equals.
equals(Object) - Method in class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
equals(Object) - Method in class edu.cmu.tetrad.search.work_in_progress.Sextad
equals(Object) - Method in class edu.cmu.tetrad.sem.ParameterPair
Checks if this ParameterPair object is equal to the specified object.
equals(Object) - Method in class edu.cmu.tetrad.sem.SemEvidence
This method checks if the given object is equal to the current instance of SemEvidence.
equals(Object) - Method in class edu.cmu.tetrad.sem.SemManipulation
Compares the current instance with the specified object for equality.
equals(Object) - Method in class edu.cmu.tetrad.sem.SemProposition
Compares this SemProposition object with the specified object for equality.
equals(Object) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedParent
equals(Object) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedFactor
equals(Object) - Method in class edu.cmu.tetrad.util.PointXy
equals(Object) - Method in class edu.cmu.tetrad.util.Vector
equals(Object) - Method in class edu.cmu.tetrad.util.Version
Equation - Class in edu.cmu.tetrad.calculator.expression
Represents an equation of the form Variable = Expression, where the Variable represents a column in some dataset.
Equation(String, Expression, String) - Constructor for class edu.cmu.tetrad.calculator.expression.Equation
Constructor for Equation.
EQUATION - Enum constant in enum class edu.cmu.tetrad.calculator.parser.Token
Equation.
ERDOS_RENYI_DAG - Static variable in class edu.cmu.tetrad.algcomparison.graph.GraphTypes
Constant ERDOS_RENYI_DAG="Erdos-Renyi DAG (Fixed Edge Probability"{trunked}
ErdosRenyi - Class in edu.cmu.tetrad.algcomparison.graph
Creates a random graph by the Erdos-Renyi method (probabiliy of edge fixed, # edges not).
ErdosRenyi() - Constructor for class edu.cmu.tetrad.algcomparison.graph.ErdosRenyi
Initializes a new instance of the ErdosRenyi class.
erf(double) - Static method in class edu.cmu.tetrad.util.StatUtils
Calculates the error function for a double
error(String) - Method in class edu.cmu.tetrad.util.TetradLogger
Logs an error, this will log the message regardless of any configuration information.
ERROR - Enum constant in enum class edu.cmu.tetrad.graph.NodeType
Constant ERROR
errorEval(Graph, Graph) - Static method in class edu.cmu.tetrad.simulation.HsimUtils
errorEval.
ERRORS_NORMAL - Static variable in class edu.cmu.tetrad.util.Params
Constant ERRORS_NORMAL="errorsNormal"
estimate() - Method in class edu.cmu.tetrad.sem.SemEstimator
Runs the estimator on the data and SemPm passed in through the constructor.
estimate() - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbs
Runs the estimator on the data and SemPm passed in through the constructor.
estimate(double[][], double[][], double) - Static method in class edu.cmu.tetrad.search.utils.EstimateRank
Estimate rank from data.
estimate(int[], int[], double[][], int, double) - Static method in class edu.cmu.tetrad.search.utils.EstimateRank
Estimate rank from covariance matrix.
estimate(BayesPm, DataSet) - Method in interface edu.cmu.tetrad.bayes.EmBayesProperties.Estimator
estimate.
estimate(BayesPm, DataSet) - Method in class edu.cmu.tetrad.bayes.MlBayesEstimator
Estimates parameters of the given Bayes net from the given data using maximum likelihood method.
estimate(BayesPm, DataSet) - Method in class edu.cmu.tetrad.bayes.MlBayesEstimatorOld
33 Estimates a Bayes IM using the variables, graph, and parameters in the given Bayes PM and the data columns in the given data set.
estimate(DirichletBayesIm, DataSet) - Static method in class edu.cmu.tetrad.bayes.DirichletEstimator
estimate.
estimate(GeneralizedSemPm, DataSet) - Method in class edu.cmu.tetrad.sem.GeneralizedSemEstimator
Maximizes likelihood equation by equation.
EstimateRank - Class in edu.cmu.tetrad.search.utils
Estimates the rank of a matrix.
estimateW(DataSet, int, double, double) - Static method in class edu.cmu.tetrad.search.IcaLingD
Estimates the W matrix using FastICA.
estimateW(DataSet, int, double, double, boolean) - Static method in class edu.cmu.tetrad.search.IcaLingD
Estimates the W matrix using FastICA.
eval(double, double) - Method in interface edu.cmu.tetrad.search.utils.Kernel
Evaluates the kernel at two points in the input space
eval(double, double) - Method in class edu.cmu.tetrad.search.utils.KernelGaussian
Evaluates the kernel at two points in the input space
evalEdges(Graph, Set<Node>, Set<Node>) - Static method in class edu.cmu.tetrad.simulation.HsimUtils
evalEdges.
evaluate(double[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.Polynomial
Evaluates the term.
evaluate(double[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialTerm
Evaluates the term.
evaluate(Context) - Method in class edu.cmu.tetrad.calculator.expression.ConstantExpression
Evaluates the expression using the given context
evaluate(Context) - Method in class edu.cmu.tetrad.calculator.expression.EvaluationExpression
Evaluates the expression using the given context
evaluate(Context) - Method in interface edu.cmu.tetrad.calculator.expression.Expression
Evaluates the expression using the given context
evaluate(Context) - Method in class edu.cmu.tetrad.calculator.expression.VariableExpression
Evaluates the expression using the given context
evaluateGeneric(Context) - Method in class edu.cmu.tetrad.calculator.expression.VariableExpression
evaluateGeneric.
EvaluationExpression - Class in edu.cmu.tetrad.calculator.expression
An equation expression.
EvaluationExpression(VariableExpression, String) - Constructor for class edu.cmu.tetrad.calculator.expression.EvaluationExpression
Constructor for EvaluationExpression.
EVENLY_DISTRIBUTED_INTERVALS - Static variable in class edu.cmu.tetrad.data.ContinuousDiscretizationSpec
Constant EVENLY_DISTRIBUTED_INTERVALS=2
EVENLY_DISTRIBUTED_VALUES - Static variable in class edu.cmu.tetrad.data.ContinuousDiscretizationSpec
The types of discretization
evenSplitVector(double, int) - Static method in class edu.pitt.csb.mgm.MixedUtils
evenSplitVector.
Evidence - Class in edu.cmu.tetrad.bayes
Stores information for a variable source about evidence we have for each variable as well as whether each variable has been manipulated.
Evidence(Evidence) - Constructor for class edu.cmu.tetrad.bayes.Evidence
Copy constructor.
Evidence(Evidence, VariableSource) - Constructor for class edu.cmu.tetrad.bayes.Evidence
Constructor for Evidence.
Evidence(Proposition) - Constructor for class edu.cmu.tetrad.bayes.Evidence
Wraps the proposition.
ExampleCompareFromFiles - Class in edu.cmu.tetrad.algcomparison.examples
An example script to load in data sets and graphs from files and analyze them.
ExampleCompareFromFiles - Class in edu.cmu.tetrad.study.examples.conditions
An example script to load in data sets and graphs from files and analyze them.
ExampleCompareSimulation - Class in edu.cmu.tetrad.algcomparison.examples
An example script to simulate data and run a comparison analysis on it.
ExampleCompareSimulation - Class in edu.cmu.tetrad.study.examples.conditions
An example script to simulate data and run a comparison analysis on it.
ExampleCompareSimulation2 - Class in edu.cmu.tetrad.algcomparison.examples
An example script to simulate data and run a comparison analysis on it.
ExampleCompareSimulationDiscrete - Class in edu.cmu.tetrad.study.examples.conditions
An example script to simulate data and run a comparison analysis on it.
ExampleCompareSimulationTimeSeries - Class in edu.cmu.tetrad.algcomparison.examples
An example script to simulate time series data and run a comparison analysis on it.
ExampleFirstInflection - Class in edu.cmu.tetrad.study.examples.conditions
An example script to simulate data and run a comparison analysis on it.
ExampleMixedSearch - Class in edu.pitt.csb.mgm
Created by ajsedgewick on 8/18/15.
ExampleNonlinearSave - Class in edu.cmu.tetrad.algcomparison.examples
An example script to save out data files and graphs from a simulation.
ExampleSave - Class in edu.cmu.tetrad.algcomparison.examples
An example script to save out data files and graphs from a simulation.
ExampleSave - Class in edu.cmu.tetrad.study.examples.conditions
An example script to save out data files and graphs from a simulation.
ExampleStars - Class in edu.cmu.tetrad.study.examples.conditions
An example script to simulate data and run a comparison analysis on it.
exhaustiveSearch(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealSearch
This method computes m/e values for all single regulators, pairs and triples at a given time lag.
exhaustiveSearch(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealSearch
This method computes m/e values for all single regulators, pairs and triples at a given time lag.
exhaustiveSearch(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealSearch
This method computes m/e values for all single regulators, pairs and triples between two time lags (inclusively).
existsCombination() - Method in class edu.cmu.tetrad.bayes.Proposition
existsCombination.
existsCommonAncestor(Graph, Edge) - Static method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorTruePositiveBidirected
Returns true if there is a common ancestor of X and Y in the graph.
existsCommonAncestor(Graph, Edge) - Static method in class edu.cmu.tetrad.algcomparison.statistic.NumCommonMeasuredAncestorBidirected
existsCommonAncestor.
existsDirectedCycle() - Method in class edu.cmu.tetrad.graph.Paths
existsDirectedCycle.
existsDirectedPath(Node, Node) - Method in class edu.cmu.tetrad.graph.Paths
Checks if a directed path exists between two nodes in a graph.
existsDirectedPath(Node, Node, int) - Method in class edu.cmu.tetrad.graph.Paths
Checks if a directed path exists between two nodes within a certain depth.
existsDirectedPath(Node, Node, Pair<Node, Node>) - Method in class edu.cmu.tetrad.graph.Paths
Checks if a directed path exists between two nodes in a graph, ignoring a specified edge.
existsDirectedPathFromTo(Graph, Node, Node) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNoMeasureAncestors
existsDirectedPathFromTo.
existsEdge(String, LaggedFactor) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Determines whether the edge to 'factor' at time lag 0 from 'laggedFactor' exists in the graph.
existsEdge(String, LaggedFactor) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Determines whether the edge to 'factor' at time lag 0 from 'laggedFactor' exists in the graph.
existsEdge(String, LaggedFactor) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Determines whether the edge to 'factor' at time lag 0 from 'laggedFactor' exists in the graph.
existsEdge(String, LaggedFactor) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Determines whether the edge to 'factor' at time lag 0 from 'laggedFactor' exists in the graph.
existsEdgeCoef(Node, Node) - Method in class edu.cmu.tetrad.sem.SemIm
existsEdgeCoef.
existsFactor(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Determines whether the given factor exists in the graph.
existsFactor(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Determines whether the given factor exists in the graph.
existsFactor(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Determines whether the given factor exists in the graph.
existsFactor(String) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Determines whether the given factor exists in the graph.
existsIn(Graph) - Method in class edu.cmu.tetrad.search.utils.DiscriminatingPath
Checks this discriminating path construct to make sure it is a discriminating path in the given graph.
existsInducingPath(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.graph.Paths
Determines whether an inducing path exists between two nodes in a graph.
existsInducingPathDFS(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.graph.Paths
Determines whether an inducing path exists between node1 and node2, given a set O of observed nodes and a set sem of conditioned nodes.
existsInducingPathInto(Node, Node, Graph, Knowledge) - Static method in class edu.cmu.tetrad.search.utils.TsDagToPag
existsInducingPathInto.
existsInducingPathVisit(Node, Node, Node, Node, Set<Node>, LinkedList<Node>) - Method in class edu.cmu.tetrad.graph.Paths
Determines whether an inducing path exists between two nodes in a graph.
existsInducingPathVisitts(Graph, Node, Node, Node, Node, LinkedList<Node>, Knowledge) - Static method in class edu.cmu.tetrad.search.utils.TsDagToPag
existsInducingPathVisitts.
existsLatentCommonAncestor(Graph, Edge) - Static method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorTruePositiveBidirected
existsLatentCommonAncestor.
existsMissingValue() - Method in class edu.cmu.tetrad.data.BoxDataSet
existsMissingValue.
existsMissingValue() - Method in interface edu.cmu.tetrad.data.DataSet
existsMissingValue.
existsMissingValue() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
existsMissingValue.
existsSemidirectedPath(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Determines whether one node is an ancestor of another.
existsSemidirectedPath(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Determines whether there is a semidirected path from node1 to node2.
existsSemiDirectedPath(Node, Node) - Method in class edu.cmu.tetrad.graph.Paths
existsSemiDirectedPath.
existsSemiDirectedPath(Node, Set<Node>) - Method in class edu.cmu.tetrad.graph.Paths
existsSemiDirectedPath.
existsTrek(Node, Node) - Method in class edu.cmu.tetrad.graph.Paths
Determines whether a trek exists between two nodes in the graph.
exp - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Score
The exp.
EXP - Static variable in class edu.cmu.tetrad.search.FastIca
The other function type that can be used to approximate negative entropy.
expandTemplate(String, GeneralizedSemPm, Node) - Method in class edu.cmu.tetrad.sem.TemplateExpander
Returns the expanded template, which needs to be checked to make sure it can be used.
experiment(String, int, int, int, double, double, boolean, boolean, double, double, String, int) - Method in class edu.cmu.tetrad.study.RBExperiments
Performs an experiment to estimate the structure and parameters of a Bayesian network using various methods.
Experimental - Interface in edu.cmu.tetrad.util
Tags a file as experimental so it's not listed in the configuration.
Experimental - Annotation Interface in edu.cmu.tetrad.annotation
Oct 17, 2017 11:40:50 AM
ExploreComparison - Class in edu.cmu.tetrad.study.performance
Runs algorithm on data set (simulation is OK), printing out error statistics.
ExploreIndepTests - Class in edu.pitt.csb.mgm
Created by ajsedgewick on 9/10/15.
Exponential - Class in edu.cmu.tetrad.util.dist
Wraps a chi square distribution for purposes of drawing random samples.
Exponential(double) - Constructor for class edu.cmu.tetrad.util.dist.Exponential
Constructor for Exponential.
Expression - Interface in edu.cmu.tetrad.calculator.expression
Represents a mathematical expression.
ExpressionDescriptor - Interface in edu.cmu.tetrad.calculator.expression
Represents a definition for some expression.
ExpressionDescriptor.Position - Enum Class in edu.cmu.tetrad.calculator.expression
An enum of positions that an expression can occur in.
ExpressionInitializationException - Exception Class in edu.cmu.tetrad.calculator.expression
Thrown if the expression can't be parsed, for instance, if it has the wrong number of arguments.
ExpressionInitializationException(String) - Constructor for exception class edu.cmu.tetrad.calculator.expression.ExpressionInitializationException
Constructor for ExpressionInitializationException.
ExpressionLexer - Class in edu.cmu.tetrad.calculator.parser
Parses the tokens of an expression.
ExpressionLexer(CharSequence) - Constructor for class edu.cmu.tetrad.calculator.parser.ExpressionLexer
Constructor for ExpressionLexer.
ExpressionManager - Class in edu.cmu.tetrad.calculator.expression
Manager for expressions, this includes all implementations of expression descriptors for the calculator.
ExpressionParser - Class in edu.cmu.tetrad.calculator.parser
Parses a string into a tree-like expression.
ExpressionParser() - Constructor for class edu.cmu.tetrad.calculator.parser.ExpressionParser
Constructrs a parser that has no allowable parameters.
ExpressionParser(Collection<String>, ExpressionParser.RestrictionType) - Constructor for class edu.cmu.tetrad.calculator.parser.ExpressionParser
Constructs the parser given a collection of allowable parameters.
ExpressionParser.RestrictionType - Enum Class in edu.cmu.tetrad.calculator.parser
The type of restriction on parameters.
ExpressionSignature - Interface in edu.cmu.tetrad.calculator.expression
Represents the signature of the expression, for example sqrt(number).
expScore(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
expScore.
expUnstandardized - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Score
The exp unstandardized.
expUnstandardizedInverted - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Score
The exp unstandardized inverted.
EXTERNAL_GRAPH - Enum constant in enum class edu.cmu.tetrad.search.FaskOrig.AdjacencyMethod
Use an external graph.
ExternalAlgorithm - Class in edu.cmu.tetrad.algcomparison.algorithm
Tags an an algorithm that loads up external graphs for inclusion in reports.
ExternalAlgorithm() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.ExternalAlgorithm
Constructor for ExternalAlgorithm.
EXTRA_EDGE_REMOVAL_STEP - Static variable in class edu.cmu.tetrad.util.Params
Constant EXTRA_EDGE_REMOVAL_STEP="extraEdgeRemovalStep"
ExtraCategoryInterpolator - Class in edu.cmu.tetrad.bayes
Returns a data set in variables for columns with missing values are augmented with an extra category that represents the missing values, with missing values being reported as belong this category.
ExtraCategoryInterpolator() - Constructor for class edu.cmu.tetrad.bayes.ExtraCategoryInterpolator
Constructs a new instance of the algorithm.
extractFactor_Display(String) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.DisplayNameHandler
Parses the given string representing a lagged factor and return the part that represents the factor.
extractLag_Display(String) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.DisplayNameHandler
Extracts the lag from the lagged factor name string.

F

F1Adj - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the F1 statistic for adjacencies.
F1Adj() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.F1Adj
Constructs a new instance of the algorithm.
F1All - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the F1 statistic for adjacencies.
F1All() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.F1All
Constructs a new instance of the algorithm.
F1Arrow - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the F1 statistic for arrowheads.
F1Arrow() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.F1Arrow
Constructs a new instance of the algorithm.
FactorAnalysis - Class in edu.cmu.tetrad.algcomparison.algorithm.other
Factor analysis.
FactorAnalysis - Class in edu.cmu.tetrad.search
Implements the classical Factor Analysis algorithm.
FactorAnalysis() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.other.FactorAnalysis
Constructs a new instance of the algorithm.
FactorAnalysis(DataSet) - Constructor for class edu.cmu.tetrad.search.FactorAnalysis
Constructor.
FactorAnalysis(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.search.FactorAnalysis
Constructor.
FactoredBayesStructuralEM - Class in edu.cmu.tetrad.bayes
Implements the procedure Factored-Bayesian-SEM found on page 6 of "The Bayesian Structural EM Algorithm" by Nir Friedman.> 0
FactoredBayesStructuralEM(DataSet, BayesPm) - Constructor for class edu.cmu.tetrad.bayes.FactoredBayesStructuralEM
Constructor for FactoredBayesStructuralEM.
factorial(int) - Static method in class edu.cmu.tetrad.util.MathUtils
factorial.
factorial(int) - Static method in class edu.cmu.tetrad.util.StatUtils
factorial.
FAITHFULNESS_ASSUMED - Static variable in class edu.cmu.tetrad.util.Params
Constant FAITHFULNESS_ASSUMED="faithfulnessAssumed"
FalseNegativesAdjacencies - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
FalseNegativesAdjacencies() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.FalseNegativesAdjacencies
Constructs a new instance of the algorithm.
FalsePositiveAdjacencies - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
FalsePositiveAdjacencies() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.FalsePositiveAdjacencies
Constructs a new instance of the algorithm.
Fas - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
Fast Adjacency Search (FAS)--i.e., the PC adjacency step, which is used in many algorithms.
Fas - Class in edu.cmu.tetrad.search
Implements the Fast Adjacency Search (FAS), which is the adjacency search of the PC algorithm (see).
Fas() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fas
Constructor for Fas.
Fas(IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fas
Constructor for Fas.
Fas(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.Fas
Constructor.
FAS_RULE - Static variable in class edu.cmu.tetrad.util.Params
Constant FAS_RULE="fasRule"
FAS_SEPSETS - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.ColliderDiscovery
FAS with sepsets reasoning.
FAS_STABLE - Enum constant in enum class edu.cmu.tetrad.search.FaskOrig.AdjacencyMethod
Fast Adjacency Search (FAS) with the stable option.
Fasd - Class in edu.cmu.tetrad.search
Adjusts FAS (see) for the deterministic case by refusing to removed edges based on conditional independence tests that are judged to be deterministic.
Fasd(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.Fasd
Constructs a new FastAdjacencySearch.
FasDci - Class in edu.cmu.tetrad.search.work_in_progress
Implements a modified version of the the "fast adjacency search" for use in the Distributed Causal Inference (DCI) algorithm.
FasDci(Graph, IndependenceTest) - Constructor for class edu.cmu.tetrad.search.work_in_progress.FasDci
Constructs a new FastAdjacencySearch for DCI.
FasDci(Graph, IndependenceTest, ResolveSepsets.Method, List<Set<Node>>, List<IndependenceTest>, SepsetMapDci, SepsetMapDci) - Constructor for class edu.cmu.tetrad.search.work_in_progress.FasDci
Constructs a new FastAdjacencySearch for DCI with independence test pooling to resolve inconsistencies.
FasFdr - Class in edu.cmu.tetrad.search.work_in_progress
Implements the "fast adjacency search" used in several causal algorithm in this package.
FasFdr(IndependenceTest, int) - Constructor for class edu.cmu.tetrad.search.work_in_progress.FasFdr
Constructs a new FastAdjacencySearch.
Fask - Class in edu.cmu.tetrad.algcomparison.algorithm.continuous.dag
FASK algorithm.
Fask - Class in edu.cmu.tetrad.search
Implements the FASK (Fast Adjacency Skewness) algorithm, which makes decisions for adjacency and orientation using a combination of conditional independence testing, judgments of nonlinear adjacency, and pairwise orientation due to non-Gaussianity.
Fask() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Constructor for Fask.
Fask(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Constructs a new Fask object with the given ScoreWrapper.
Fask(DataSet, Score) - Constructor for class edu.cmu.tetrad.search.Fask
Constructs a new instance of the FaskOrig class with the given DataSet and Score objects.
FASK_ADJACENCY_METHOD - Static variable in class edu.cmu.tetrad.util.Params
Constant FASK_ADJACENCY_METHOD="faskAdjacencyMethod"
FASK_DELTA - Static variable in class edu.cmu.tetrad.util.Params
Constant FASK_DELTA="faskDelta"
FASK_LEFT_RIGHT_RULE - Static variable in class edu.cmu.tetrad.util.Params
Constant FASK_LEFT_RIGHT_RULE="faskLeftRightRule"
FASK_NONEMPIRICAL - Static variable in class edu.cmu.tetrad.util.Params
Constant FASK_NONEMPIRICAL="faskNonempirical"
Fask.LeftRight - Enum Class in edu.cmu.tetrad.search
Enumerates the options left-right rules to use for FASK.
FASK1 - Enum constant in enum class edu.cmu.tetrad.search.Fask.LeftRight
The original FASK left-right rule.
FASK1 - Enum constant in enum class edu.cmu.tetrad.search.FaskOrig.LeftRight
The original FASK left-right rule.
FASK2 - Enum constant in enum class edu.cmu.tetrad.search.Fask.LeftRight
The modified FASK left-right rule.
FASK2 - Enum constant in enum class edu.cmu.tetrad.search.FaskOrig.LeftRight
The modified FASK left-right rule.
FaskConcatenated - Class in edu.cmu.tetrad.algcomparison.algorithm.multi
Wraps the IMaGES algorithm for continuous variables.
FaskConcatenated() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Constructor for FaskConcatenated.
FaskConcatenated(ScoreWrapper, IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Constructor for FaskConcatenated.
faskLeftRightV1(double[], double[], boolean, double) - Static method in class edu.cmu.tetrad.search.FaskOrig
Calculates the left-right ratio using the Fask method version 1.
faskLeftRightV2(double[], double[], boolean, double) - Static method in class edu.cmu.tetrad.search.FaskOrig
Calculates the left-right judgment for two arrays of double values.
FaskLofsConcatenated - Class in edu.cmu.tetrad.algcomparison.algorithm.multi
Wraps the IMaGES algorithm for continuous variables.
FaskLofsConcatenated(Lofs.Rule) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskLofsConcatenated
Constructor for FaskLofsConcatenated.
FaskOrig - Class in edu.cmu.tetrad.algcomparison.algorithm.continuous.dag
The FaskOrig class is an implementation of the FASK-Orig algorithm for causal discovery.
FaskOrig - Class in edu.cmu.tetrad.search
Implements the FASK (Fast Adjacency Skewness) algorithm, which makes decisions for adjacency and orientation using a combination of conditional independence testing, judgments of nonlinear adjacency, and pairwise orientation due to non-Gaussianity.
FaskOrig() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Constructor for Fask.
FaskOrig(IndependenceWrapper, ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Constructor for Fask.
FaskOrig(DataSet, Score, IndependenceTest) - Constructor for class edu.cmu.tetrad.search.FaskOrig
Constructor.
FaskOrig.AdjacencyMethod - Enum Class in edu.cmu.tetrad.search
Enumerates the alternatives to use for finding the initial adjacencies for FASK.
FaskOrig.LeftRight - Enum Class in edu.cmu.tetrad.search
Enumerates the options left-right rules to use for FASK.
FaskPw - Class in edu.cmu.tetrad.algcomparison.algorithm.pairwise
FASK-PW (pairwise).
FaskPw() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.FaskPw
Constructor for FaskPw.
FaskPw(Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.FaskPw
Constructor for FaskPw.
FaskVote - Class in edu.cmu.tetrad.algcomparison.algorithm.multi
Wraps the MultiFask algorithm for continuous variables.
FaskVote - Class in edu.cmu.tetrad.search.work_in_progress
Runs IMaGES on a list of algorithms and then produces a graph over the ImaGES adjacencies where each edge orientation is voted on by running FASK on each dataset in turn and voting on edge orientation.
FaskVote() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Constructor for FaskVote.
FaskVote(IndependenceWrapper, ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Constructor for FaskVote.
FaskVote(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Constructor for FaskVote.
FaskVote(List<DataSet>, ScoreWrapper, IndependenceWrapper) - Constructor for class edu.cmu.tetrad.search.work_in_progress.FaskVote
Constructor.
FasLofs - Class in edu.cmu.tetrad.algcomparison.algorithm.multi
Wraps the IMaGES algorithm for continuous variables.
FasLofs - Class in edu.cmu.tetrad.search.work_in_progress
Runs Fast Adjacency Search (FAS) and then orients each edge using the robust skew orientation algorithm.
FasLofs(DataSet, Lofs.Rule) - Constructor for class edu.cmu.tetrad.search.work_in_progress.FasLofs
Constructor for FasLofs.
FasLofs(Lofs.Rule) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FasLofs
Constructor for FasLofs.
FAST_ICA_A - Static variable in class edu.cmu.tetrad.util.Params
Constant FAST_ICA_A="fastIcaA"
FAST_ICA_MAX_ITER - Static variable in class edu.cmu.tetrad.util.Params
Constant FAST_ICA_MAX_ITER="fastIcaMaxIter"
FAST_ICA_TOLERANCE - Static variable in class edu.cmu.tetrad.util.Params
Constant FAST_ICA_TOLERANCE="fastIcaTolerance"
FastIca - Class in edu.cmu.tetrad.search
Translates a version of the FastICA algorithm used in R from Fortran into Java for use in Tetrad.
FastIca(Matrix, int) - Constructor for class edu.cmu.tetrad.search.FastIca
Constructs an instance of the Fast ICA algorithm, taking as arguments the two arguments that cannot be defaulted: the data matrix itself and the number of components to be extracted.
FastICA - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The FastICA rule.
FastIca.IcaResult - Class in edu.cmu.tetrad.search
A list containing the following components
FBetaAdj - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the F1 statistic for adjacencies.
FBetaAdj() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.FBetaAdj
Constructs a new instance of the algorithm.
fCdf(double, double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
F CDF.
Fci - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
The Fast Causal Inference (FCI) algorithm.
Fci - Class in edu.cmu.tetrad.search
Implements the Fast Causal Inference (FCI) algorithm due to Peter Spirtes, which addressed the case where latent common causes cannot be assumed not to exist with respect to the data set being analyzed.
Fci() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci
Constructor.
Fci(IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci
Constructor.
Fci(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.Fci
Constructor.
Fci(IndependenceTest, List<Node>) - Constructor for class edu.cmu.tetrad.search.Fci
Constructor.
FCI - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.Algorithm
Constant for the FCI algorithm.
FciIod - Class in edu.cmu.tetrad.algcomparison.algorithm.multi
Runs FCI on multiple datasets using the IOD pooled dataset independence test.
FciIod() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Constructor for FciIod.
FciIod(IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Constructor for FciIod.
FciMax - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
FCI-Max algorithm.
FciMax - Class in edu.cmu.tetrad.search
Modifies FCI to do orientation of unshielded colliders (X*-*Y*-*Z with X and Z not adjacent) using the max-P rule (see the PC-Max algorithm).
FciMax() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax
Constructor for FciMax.
FciMax(IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax
Constructor for FciMax.
FciMax(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.FciMax
Constructor.
FciOrient - Class in edu.cmu.tetrad.search.utils
Performs the final orientation steps of the FCI algorithms, which is a useful tool to use in a variety of FCI-like algorithms.
FciOrient(R0R4Strategy) - Constructor for class edu.cmu.tetrad.search.utils.FciOrient
Initializes a new instance of the FciOrient class with the specified R4Strategy.
fciOrientbk(Knowledge, Graph, List<Node>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Attempts to orient the edges in the graph based on the given knowledge.
fciOrientbk(Knowledge, Graph, List<Node>) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Orient the edges of a graph based on the given knowledge.
FciOrientDijkstra - Class in edu.cmu.tetrad.search
A simple implementation of Dijkstra's algorithm for finding the shortest path in a graph.
FciOrientDijkstra.DijkstraEdge - Class in edu.cmu.tetrad.search
Represents a node in Dijkstra's algorithm.
FciOrientDijkstra.Graph - Class in edu.cmu.tetrad.search
Represents a graph for Dijkstra's algorithm.
fdr - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
False discovery rate method
fdr - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
The fdr method.
fdr(double, List<Double>) - Static method in class edu.cmu.tetrad.util.StatUtils
fdr.
fdr(double, List<Double>, boolean, boolean) - Static method in class edu.cmu.tetrad.util.StatUtils
fdr.
fdrCutoff(double, List<Double>, boolean) - Static method in class edu.cmu.tetrad.util.StatUtils
fdrCutoff.
fdrCutoff(double, List<Double>, boolean, boolean) - Static method in class edu.cmu.tetrad.util.StatUtils
Calculates the cutoff value for p-values using the FDR method.
fdrCutoff(double, List<Double>, int[], boolean, boolean) - Static method in class edu.cmu.tetrad.util.StatUtils
fdrCutoff.
fdrQ(List<Double>, int) - Static method in class edu.cmu.tetrad.util.StatUtils
fdrQ.
Fges - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
FGES (the heuristic version).
Fges - Class in edu.cmu.tetrad.search
Implements the Fast Greedy Equivalence Search (FGES) algorithm.
Fges() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges
Constructor for Fges.
Fges(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges
Constructor for Fges.
Fges(Score) - Constructor for class edu.cmu.tetrad.search.Fges
Constructor.
FGES - Enum constant in enum class edu.cmu.tetrad.search.Cstar.CpdagAlgorithm
The FGES algorithm.
FGES - Enum constant in enum class edu.cmu.tetrad.search.FaskOrig.AdjacencyMethod
FGES with the BIC score.
FGES - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.Algorithm
Constant for the FGES algorithm.
FgesConcatenated - Class in edu.cmu.tetrad.algcomparison.algorithm.multi
Requires that the parameter 'randomSelectionSize' be set to indicate how many datasets should be taken at a time (randomly).
FgesConcatenated(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Constructor for FgesConcatenated.
FgesConcatenated(ScoreWrapper, boolean) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Constructor for FgesConcatenated.
FgesConcatenated(ScoreWrapper, Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Constructor for FgesConcatenated.
FgesMb - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
FGES-MB (the heuristic version).
FgesMb - Class in edu.cmu.tetrad.search
Implements the Fast Greedy Equivalence Search (FGES) algorithm.
FgesMb() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMb
Constructor for FgesMb.
FgesMb(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMb
Constructor for FgesMb.
FgesMb(Score) - Constructor for class edu.cmu.tetrad.search.FgesMb
Constructor.
FgesMeasurement - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
FGES (the heuristic version).
FgesMeasurement(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMeasurement
Constructor for FgesMeasurement.
FgesOrienter - Class in edu.cmu.tetrad.search.utils
This Orients a given undirected graph such that the edges in the graph are a superset of the edges in the oriented graph, using FGES method.
FgesOrienter(DataSet) - Constructor for class edu.cmu.tetrad.search.utils.FgesOrienter
The data set must either be all continuous or all discrete.
FgesWrapper(double...) - Constructor for class edu.pitt.csb.stability.SearchWrappers.FgesWrapper
Constructor.
Fgls - Enum constant in enum class edu.cmu.tetrad.sem.ScoreType
The FGLS score
fifthMoment - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Score
The fifth moment.
FILE_OUT_PATH - Static variable in class edu.cmu.tetrad.util.Params
Constant FILE_OUT_PATH="fileOutPath"
fillIn(Graph, Node[]) - Static method in class edu.cmu.tetrad.bayes.GraphTools
Apply Tarjan and Yannakakis (1984) fill in algorithm for graph triangulation.
filter(DataSet) - Method in class edu.cmu.tetrad.bayes.ExtraCategoryInterpolator
Interpolates the given data set, producing a data set with no missing values.
filter(DataSet) - Method in class edu.cmu.tetrad.bayes.ModeInterpolator
Interpolates the given data set, producing a data set with no missing values.
filter(DataSet) - Method in class edu.cmu.tetrad.data.CaseExpander
Interpolates the given data set, producing a data set with no missing values.
filter(DataSet) - Method in interface edu.cmu.tetrad.data.DataFilter
Interpolates the given data set, producing a data set with no missing values.
filter(DataSet) - Method in class edu.cmu.tetrad.data.MeanInterpolator
Interpolates the given data set, producing a data set with no missing values.
filterByAnnotation(List<AnnotatedClass<T>>, Class<? extends Annotation>) - Method in class edu.cmu.tetrad.annotation.AbstractAnnotations
Filter annotated classes by annotation type.
filterByAnnotations(Class<? extends Annotation>, List<AnnotatedClass<T>>) - Static method in class edu.cmu.tetrad.annotation.AnnotatedClassUtils
Filters a list of annotated classes by the given annotation.
filterOutByAnnotation(List<AnnotatedClass<T>>, Class<? extends Annotation>) - Method in class edu.cmu.tetrad.annotation.AbstractAnnotations
Filter out annotated classes by annotation type.
filterOutExperimental(List<AnnotatedClass<Algorithm>>) - Method in class edu.cmu.tetrad.annotation.AlgorithmAnnotations
Filters out algorithms that are not for the given data type.
filterOutExperimental(List<AnnotatedClass<Score>>) - Method in class edu.cmu.tetrad.annotation.ScoreAnnotations
filterOutExperimental.
filterOutExperimental(List<AnnotatedClass<TestOfIndependence>>) - Method in class edu.cmu.tetrad.annotation.TestOfIndependenceAnnotations
filterOutExperimental.
finalOrientation(Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Orients the graph (in place) according to rules in the graph (FCI step D).
FIND_ONE_FACTOR_CLUSTERS - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcAlgorithmType
FOFC algorithm
FIND_TWO_FACTOR_CLUSTERS - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcAlgorithmType
FTFC algorithm.
findCliques(int[][], int) - Static method in class edu.cmu.tetrad.graph.Paths.AllCliquesAlgorithm
Find all cliques in a graph.
findComponents() - Method in class edu.cmu.tetrad.search.FastIca
Runs the Fast ICA algorithm (following the R version) and returns the list of result items that the R version returns.
findHittingSet(List<Set<GraphChange>>) - Static method in class edu.cmu.tetrad.search.work_in_progress.IonHittingSet
takes a List of HashSets of GraphChanges, and returns a List of GraphChanges.
findMb(Node) - Method in class edu.cmu.tetrad.search.GrowShrink
Finds the Markov blanket (MB) for a given target node.
findMb(Node) - Method in interface edu.cmu.tetrad.search.IMbSearch
Given the target, this returns all the nodes in the Markov Blanket.
findMb(Node) - Method in class edu.cmu.tetrad.search.PcMb
Given the target, this returns all the nodes in the Markov Blanket.
findMb(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.Iamb
Given the target, this returns all the nodes in the Markov Blanket.
findMb(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.IambnPc
Given the target, this returns all the nodes in the Markov Blanket.
findMb(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.InterIamb
Given the target, this returns all the nodes in the Markov Blanket.
findMb(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.Mmmb
Given the target, this returns all the nodes in the Markov Blanket.
findMConnectingPaths(Graph, Node, Node, Collection<Node>) - Static method in class edu.cmu.tetrad.search.utils.PossibleMConnectingPath
Finds all possible D-connection undirectedPaths as sub-graphs of the pag given at construction time from x to y given z.
findMConnectingPathsOfLength(Graph, Node, Node, Collection<Node>, Integer) - Static method in class edu.cmu.tetrad.search.utils.PossibleMConnectingPath
Finds all possible D-connection undirectedPaths as sub-graphs of the pag given at construction time from x to y given z for a particular path length.
findOptimalAssignment() - Method in class edu.cmu.tetrad.search.utils.HungarianAlgorithm
find an optimal assignment
findTerm(int[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.Polynomial
Finds the first term matching the given profile.
fine(String) - Method in class edu.cmu.tetrad.util.LogUtils
fine.
finer(String) - Method in class edu.cmu.tetrad.util.LogUtils
finer.
finest(String) - Method in class edu.cmu.tetrad.util.LogUtils
finest.
FirstInflection - Class in edu.cmu.tetrad.algcomparison.algorithm
First inflection point.
FirstInflection(Algorithm, String, double, double, double) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.FirstInflection
Constructor for FirstInflection.
fisher - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Fisher's method
fisher - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
The fisher method.
FISHER_EPSILON - Static variable in class edu.cmu.tetrad.util.Params
Constant FISHER_EPSILON="fisherEpsilon"
fisher2 - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Fisher's method
fisher2 - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
The fisher method with only available p values.
FisherZ - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Fisher Z test.
FisherZ - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.IndependenceTestType
Constant for the FisherZ independence test.
FisherZ() - Constructor for class edu.cmu.tetrad.algcomparison.independence.FisherZ
Constructs a new instance of the algorithm.
FisherZScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for Fisher Z test.
FisherZScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.FisherZScore
Constructs a new instance of the algorithm.
fit(DataSet) - Method in class edu.cmu.tetrad.search.IcaLingam
Fits an ICA-LiNGAM model to the given dataset using a default method for estimating W.
fit(DataSet) - Method in class edu.cmu.tetrad.search.IcaLingD
Fits a LiNG-D model to the given dataset using a default method for estimating W.
FitConGraphResult(DoubleMatrix2D, double, int, int) - Constructor for class edu.cmu.tetrad.sem.Ricf.FitConGraphResult
The result.
fixLatentErrorVariances() - Method in class edu.cmu.tetrad.sem.SemPm
fixLatentErrorVariances.
fixLatents1(int, Graph) - Static method in class edu.cmu.tetrad.graph.RandomGraph
fixLatents1.
fixLatents4(int, Graph) - Static method in class edu.cmu.tetrad.graph.RandomGraph
fixLatents4.
fixOneLoadingPerLatent() - Method in class edu.cmu.tetrad.sem.SemPm
fixOneLoadingPerLatent.
flatten(DoubleMatrix2D) - Static method in class edu.pitt.csb.mgm.Mgm
flatten.
FloatDataBox - Class in edu.cmu.tetrad.data
Stores a 2D array of float data.
FloatDataBox(float[][]) - Constructor for class edu.cmu.tetrad.data.FloatDataBox
Constructs a new data box using the given 2D float data array as data.
flush() - Method in class edu.cmu.tetrad.util.TetradLogger
Flushes the writers.
Fml - Enum constant in enum class edu.cmu.tetrad.sem.ScoreType
The FML score
Fofc - Class in edu.cmu.tetrad.algcomparison.algorithm.cluster
Find One Factor Clusters.
Fofc - Class in edu.cmu.tetrad.search
Implements the Find One Factor Clusters (FOFC) algorithm by Erich Kummerfeld, which uses reasoning about vanishing tetrads of algorithms to infer clusters of the measured variables in a dataset that each be explained by a single latent variable.
Fofc() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.cluster.Fofc
Constructor for Fofc.
Fofc(DataSet, BpcTestType, Fofc.Algorithm, double) - Constructor for class edu.cmu.tetrad.search.Fofc
Conctructor.
Fofc(ICovarianceMatrix, BpcTestType, Fofc.Algorithm, double) - Constructor for class edu.cmu.tetrad.search.Fofc
Constructor.
Fofc.Algorithm - Enum Class in edu.cmu.tetrad.search
Gives the options to be used in FOFC to sort through the various possibilities for forming clusters to find the best options.
forbid_latent_common_causes - Enum constant in enum class edu.cmu.tetrad.annotation.AlgType
If an algorithm forbids latent common causes.
FORBIDDEN - Static variable in class edu.cmu.tetrad.data.KnowledgeGroup
Constant FORBIDDEN=2
forbiddenEdgesIterator() - Method in class edu.cmu.tetrad.data.Knowledge
Iterator over the KnowledgeEdge's representing forbidden edges.
forbiddenViolations(Graph, Knowledge) - Static method in class edu.cmu.tetrad.search.CheckKnowledge
Returns a sorted list of edges that violate the given knowledge.
formatErrorsArray(double[], String) - Static method in class edu.cmu.tetrad.simulation.HsimUtils
formatErrorsArray.
fPdf(double, double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
fPdf.
fQuantile(double, double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
fQuantile.
fracDepDep() - Method in record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Returns the value of the fracDepDep record component.
fracDepInd() - Method in record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Returns the value of the fracDepInd record component.
FractionDependentUnderAlternative - Class in edu.cmu.tetrad.algcomparison.statistic
Estimates whether the p-values under the null are Uniform usign the Markov Checker.
FractionDependentUnderAlternative() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderAlternative
Constructor for FractionDependentUnderAlternative.
FractionDependentUnderAlternative(double) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderAlternative
Constructor for FractionDependentUnderAlternative.
FractionDependentUnderNull - Class in edu.cmu.tetrad.algcomparison.statistic
Estimates whether the p-values under the null are Uniform usign the Markov Checker.
FractionDependentUnderNull() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderNull
Constructor for FractionDependentUnderNull.
FractionDependentUnderNull(double) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderNull
Constructor for FractionDependentUnderNull.
fRand(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
F distribution random generator.
fruchtermanReingoldLayout(Graph) - Static method in class edu.cmu.tetrad.graph.LayoutUtil
fruchtermanReingoldLayout.
FruchtermanReingoldLayout(Graph) - Constructor for class edu.cmu.tetrad.graph.LayoutUtil.FruchtermanReingoldLayout
Constructs a new FruchtermanReingoldLayout for the given graph.
Ftfc - Class in edu.cmu.tetrad.algcomparison.algorithm.cluster
FTFC.
Ftfc - Class in edu.cmu.tetrad.search
Implements the Find Two Factor Clusters (FOFC) algorithm, which uses reasoning about vanishing tetrads of algorithms to infer clusters of the measured variables in a dataset that each be explained by a single latent variable.
Ftfc() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.cluster.Ftfc
Constructor for Ftfc.
Ftfc(DataSet, Ftfc.Algorithm, double) - Constructor for class edu.cmu.tetrad.search.Ftfc
Conctructor.
Ftfc(ICovarianceMatrix, Ftfc.Algorithm, double) - Constructor for class edu.cmu.tetrad.search.Ftfc
Conctructor.
Ftfc.Algorithm - Enum Class in edu.cmu.tetrad.search
Gives the options to be used in FOFC to sort through the various possibilities for forming clusters to find the best options.
fullyConnect(Endpoint) - Method in class edu.cmu.tetrad.graph.Dag
Fully connects the given endpoint.
fullyConnect(Endpoint) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Removes all edges from the graph and fully connects it using #-# edges, where # is the given endpoint.
fullyConnect(Endpoint) - Method in interface edu.cmu.tetrad.graph.Graph
Removes all edges from the graph and fully connects it using #-# edges, where # is the given endpoint.
fullyConnect(Endpoint) - Method in class edu.cmu.tetrad.graph.LagGraph
Removes all edges from the graph and fully connects it using #-# edges, where # is the given endpoint.
fullyConnect(Endpoint) - Method in class edu.cmu.tetrad.graph.SemGraph
Removes all edges from the graph and fully connects it using #-# edges, where # is the given endpoint.
fullyConnect(Endpoint) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Fully connects the given endpoint to all other endpoints in the graph.
Function - Interface in edu.cmu.tetrad.util
Interface for a single-argument, double-valued function that can be passed to mathematical routines.
futureNodeVisit(Graph, Node, LinkedList<Node>, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
futureNodeVisit.
futureNodeVisit(Graph, Node, LinkedList<Node>, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
futureNodeVisit.
futureNodeVisit(Graph, Node, LinkedList<Node>, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.VcPc
futureNodeVisit.
futureNodeVisit(Graph, Node, LinkedList<Node>, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
futureNodeVisit.
futureNodeVisit(Graph, Node, LinkedList<Node>, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
futureNodeVisit.

G

g(double) - Static method in class edu.cmu.tetrad.search.FaskOrig
Calculates the logarithm of the hyperbolic cosine of the maximum of x and 0.
G_SQUARE - Enum constant in enum class edu.cmu.tetrad.search.test.ChiSquareTest.TestType
The G-square test.
gamma(double) - Static method in class edu.cmu.tetrad.util.StatUtils
GAMMA FUNCTION (From DStat, used by permission).
Gamma - Class in edu.cmu.tetrad.util.dist
Wraps a chi square distribution for purposes of drawing random samples.
gammaCdf(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
compute complementary gamma cdf by its continued fraction expansion
gammaPdf(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
gammaPdf.
gammaQuantile(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
gammaQuantile.
gammaRand(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
Gamma random generator.
GAP - Enum constant in enum class edu.cmu.tetrad.search.Fofc.Algorithm
The GAP algorithm.
GAP - Enum constant in enum class edu.cmu.tetrad.search.Ftfc.Algorithm
The GAP algorithm.
GAP - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
GAP test, for FTFC.
Gaussian - Annotation Interface in edu.cmu.tetrad.annotation
Data are normal distributed.
GAUSSIAN - Enum constant in enum class edu.cmu.tetrad.search.test.Kci.KernelType
 
GAUSSIAN_FACTOR - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
Gaussian Factor.
GAUSSIAN_PVALUE - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
This one will work and does a good job for medium sized models.
GAUSSIAN_SCORE - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
This is very slow.
GAUSSIAN_SCORE_ITERATE - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
Even slower.
GAUSSIAN_SCORE_MARKS - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
This will work and does a good job for small models, no more than 4 latents.
GaussianCategoricalIm(GeneralizedSemPm) - Static method in class edu.pitt.csb.mgm.MixedUtils
GaussianCategoricalIm.
GaussianCategoricalIm(GeneralizedSemPm, boolean) - Static method in class edu.pitt.csb.mgm.MixedUtils
This method is needed to normalize edge parameters for an Instantiated Mixed Model Generates edge parameters for c-d and d-d edges from a single weight, abs(w), drawn by the normal IM constructor.
GaussianCategoricalPm(Graph, String) - Static method in class edu.pitt.csb.mgm.MixedUtils
GaussianCategoricalPm.
GaussianPower - Class in edu.cmu.tetrad.util.dist
GaussianPower class.
GaussianPower(double) - Constructor for class edu.cmu.tetrad.util.dist.GaussianPower
Constructor for GaussianPower.
GaussianTrinaryPm(Graph, HashMap<String, String>, int, String) - Static method in class edu.pitt.csb.mgm.MixedUtils
GaussianTrinaryPm.
Gdistance - Class in edu.cmu.tetrad.simulation
Created by Erich on 7/3/2016.
Gdistance(DataSet, double, double, double) - Constructor for class edu.cmu.tetrad.simulation.Gdistance
Constructor for Gdistance.
GdistanceApply - Class in edu.cmu.tetrad.simulation
Created by Erich on 7/14/2016.
GdistanceRandom - Class in edu.cmu.tetrad.simulation
Created by Erich on 8/6/2016.
GdistanceRandom(DataSet) - Constructor for class edu.cmu.tetrad.simulation.GdistanceRandom
Constructor for GdistanceRandom.
GdistanceRandomApply - Class in edu.cmu.tetrad.simulation
Created by Erich on 8/6/2016.
GdistanceTest - Class in edu.cmu.tetrad.simulation
Created by Erich on 7/6/2016.
GdistanceUtils - Class in edu.cmu.tetrad.simulation
Created by Erich on 8/11/2016.
Gene(int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch.Gene
Constructor for Gene.
GeneHistory - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Implements the basic machinery used by all history objects.
GeneHistory(Initializer, UpdateFunction) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Constructs a new history with the given initializer and the given update function.
GenePm - Class in edu.cmu.tetrad.study.gene.tetradapp.model
Implements a parametric gene model.
GenePm(LagGraph) - Constructor for class edu.cmu.tetrad.study.gene.tetradapp.model.GenePm
Construct a new gene pm, wrapping the given lag graph.
General - Annotation Interface in edu.cmu.tetrad.annotation
Data with variables of general distribution.
GENERAL_SEM_ERROR_TEMPLATE - Static variable in class edu.cmu.tetrad.util.Params
Constant GENERAL_SEM_ERROR_TEMPLATE="generalSemErrorTemplate"
GENERAL_SEM_FUNCTION_TEMPLATE_LATENT - Static variable in class edu.cmu.tetrad.util.Params
Constant GENERAL_SEM_FUNCTION_TEMPLATE_LATENT="generalSemFunctionTemplateLatent"
GENERAL_SEM_FUNCTION_TEMPLATE_MEASURED - Static variable in class edu.cmu.tetrad.util.Params
Constant GENERAL_SEM_FUNCTION_TEMPLATE_MEASURED="generalSemFunctionTemplateMeasured"
GENERAL_SEM_PARAMETER_TEMPLATE - Static variable in class edu.cmu.tetrad.util.Params
Constant GENERAL_SEM_PARAMETER_TEMPLATE="generalSemParameterTemplate"
GENERAL_STRUCTURAL_EQUATION_MODEL - Static variable in class edu.cmu.tetrad.algcomparison.simulation.SimulationTypes
Constant GENERAL_STRUCTURAL_EQUATION_MODEL="General Structural Equation Model"
GeneralAndersonDarlingTest - Class in edu.cmu.tetrad.data
Implements the Anderson-Darling test against the given CDF, with P values calculated as in R's ad.test method (in package nortest).
GeneralAndersonDarlingTest(List<Double>, RealDistribution) - Constructor for class edu.cmu.tetrad.data.GeneralAndersonDarlingTest
Constructs an Anderson-Darling test for the given column of data.
GeneralizedSemEstimator - Class in edu.cmu.tetrad.sem
Estimates a Generalized SEM I'M given a Generalized SEM PM and a data set.
GeneralizedSemEstimator() - Constructor for class edu.cmu.tetrad.sem.GeneralizedSemEstimator
Constructs a new GeneralizedSemEstimator.
GeneralizedSemEstimator.MyContext - Class in edu.cmu.tetrad.sem
Context.
GeneralizedSemIm - Class in edu.cmu.tetrad.sem
Represents a generalized SEM-instantiated model.
GeneralizedSemIm(GeneralizedSemPm) - Constructor for class edu.cmu.tetrad.sem.GeneralizedSemIm
Constructs a new GeneralizedSemIm from the given GeneralizedSemPm by picking values for each of the freeParameters from their initial distributions.
GeneralizedSemIm(GeneralizedSemPm, SemIm) - Constructor for class edu.cmu.tetrad.sem.GeneralizedSemIm
Initializes a GeneralizedSemIm object by applying values to free parameters from the given GeneralizedSemPm and SemIm.
GeneralizedSemPm - Class in edu.cmu.tetrad.sem
Parametric model for a Generalized SEM model.
GeneralizedSemPm(Graph) - Constructor for class edu.cmu.tetrad.sem.GeneralizedSemPm
Constructs a BayesPm from the given Graph, which must be convertible first into a ProtoSemGraph and then into a SemGraph.
GeneralizedSemPm(SemGraph) - Constructor for class edu.cmu.tetrad.sem.GeneralizedSemPm
Constructs a new SemPm from the given SemGraph.
GeneralizedSemPm(GeneralizedSemPm) - Constructor for class edu.cmu.tetrad.sem.GeneralizedSemPm
Initializes a new instance of the GeneralizedSemPm class by copying the properties of the provided GeneralizedSemPm object.
GeneralizedSemPm(SemPm) - Constructor for class edu.cmu.tetrad.sem.GeneralizedSemPm
Constructs a new GeneralizedSemPm object based on the given SemPm object.
GeneralSemSimulation - Class in edu.cmu.tetrad.algcomparison.simulation
The GeneralSemSimulation class represents a simulation using a generalized structural equation model (SEM).
GeneralSemSimulation(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Constructs a GeneralSemSimulation object with the given RandomGraph object.
GeneralSemSimulation(GeneralizedSemIm) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Constructs a GeneralSemSimulation object with the given GeneralizedSemIm object.
GeneralSemSimulation(GeneralizedSemPm) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Initializes a GeneralSemSimulation with the given GeneralizedSemPm object.
GeneralSemSimulationSpecial1 - Class in edu.cmu.tetrad.algcomparison.simulation
This was used for a simulation to test the FTFC and FOFC algorithm and contains some carefully selected functions to test nonlinearity and non-Gaussianity.
GeneralSemSimulationSpecial1(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1
Constructor for GeneralSemSimulationSpecial1.
generate() - Method in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Generates a random graph.
generate(Graph) - Static method in class edu.cmu.tetrad.bayes.ModelGenerator
This method takes an acyclic graph as input and returns a list of graphs each of which is a modification of the original graph with either an edge deleted, added or reversed.
generateCpdagDags(Graph, boolean) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Generates the list of DAGs in the given cpdag.
generateLatentNames(int) - Static method in class edu.cmu.tetrad.search.utils.ClusterUtils
Generates a list of latent variable names.
generateMbDags(Graph, boolean, IndependenceTest, int, Node) - Static method in class edu.cmu.tetrad.search.utils.MbUtils
Generates the list of MB DAGs consistent with the MB CPDAG returned by the previous search.
generateMixedEdgeParams(double, int) - Static method in class edu.pitt.csb.mgm.MixedUtils
generateMixedEdgeParams.
generateReportFromExternalAlgorithms(String, String, Algorithms, Statistics, Parameters) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Generates a report from external algorithms.
generateReportFromExternalAlgorithms(String, String, Algorithms, Statistics, Parameters, long, TimeUnit) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
generateReportFromExternalAlgorithms.
generateReportFromExternalAlgorithms(String, String, String, Algorithms, Statistics, Parameters) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Generates a report from external algorithms based on the given parameters.
generateReportFromExternalAlgorithms(String, String, String, Algorithms, Statistics, Parameters, long, TimeUnit) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
generateReportFromExternalAlgorithms.
generateResults(boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
Generates all results, for both the Markov and dependency checks, for each node in the graph given the parents of that node.
generateResults(boolean, boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
Generates results based on the specified independence and clearing conditions.
get(int) - Method in class edu.cmu.tetrad.data.DataModelList
get(int) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns the node at index j in pi.
get(int) - Method in class edu.cmu.tetrad.util.Vector
get.
get(int, int) - Method in interface edu.cmu.tetrad.bayes.CptMap
Retrieves the value at the specified row and column in the CptMap.
get(int, int) - Method in class edu.cmu.tetrad.bayes.CptMapCounts
Returns the probability of the node taking on the value specified by the given row and column.
get(int, int) - Method in class edu.cmu.tetrad.bayes.CptMapProbs
Returns the probability of the node taking on the value specified by the given row and column.
get(int, int) - Method in class edu.cmu.tetrad.data.ByteDataBox
get.
get(int, int) - Method in interface edu.cmu.tetrad.data.DataBox
get.
get(int, int) - Method in class edu.cmu.tetrad.data.DoubleDataBox
get.
get(int, int) - Method in class edu.cmu.tetrad.data.FloatDataBox
get.
get(int, int) - Method in class edu.cmu.tetrad.data.IntDataBox
get.
get(int, int) - Method in class edu.cmu.tetrad.data.LongDataBox
get.
get(int, int) - Method in class edu.cmu.tetrad.data.MixedDataBox
get.
get(int, int) - Method in class edu.cmu.tetrad.data.ShortDataBox
get.
get(int, int) - Method in class edu.cmu.tetrad.data.VerticalDoubleDataBox
get.
get(int, int) - Method in class edu.cmu.tetrad.data.VerticalIntDataBox
get.
get(int, int) - Method in class edu.cmu.tetrad.util.Matrix
get.
get(Node) - Method in class edu.cmu.tetrad.search.utils.SepsetMap
Returns the parents of the node x.
get(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
get.
get(Node, Node) - Method in class edu.cmu.tetrad.search.utils.SepsetMap
Retrieves the sepset previously set for {a, b}, or null if no such set was previously set.
get(Node, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
Retrieves the sepset previously set for {x, y}, or null if no such set was previously set.
get(String) - Method in class edu.cmu.tetrad.util.AlgorithmDescriptions
Gets the description of the algorithm.
get(String) - Method in class edu.cmu.tetrad.util.IndependenceTestDescriptions
get.
get(String) - Method in class edu.cmu.tetrad.util.ParamDescriptions
get.
get(String) - Method in class edu.cmu.tetrad.util.Parameters
Returns the object value of the given parameter, looking up its default in the ParamDescriptions map.
get(String) - Method in class edu.cmu.tetrad.util.ScoreDescriptions
get.
get(String, Object) - Method in class edu.cmu.tetrad.util.Parameters
Returns the object value of the given parameter, using the given default.
getA() - Method in class edu.cmu.tetrad.search.utils.Bes.Arrow
Returns the first node.
getA() - Method in class edu.cmu.tetrad.sem.ParameterPair
Method getNumObjects
getA() - Method in class edu.cmu.tetrad.util.ChoiceGenerator
Getter for the field a.
getA() - Method in class edu.cmu.tetrad.util.dist.Split
Getter for the field a.
getA() - Method in class edu.cmu.tetrad.util.SelectionGenerator
Getter for the field a.
getA() - Method in class edu.cmu.tetrad.util.SublistGenerator
Getter for the field a.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFn
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFp
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFpr
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyPrecision
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyRecall
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTn
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTp
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTpr
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorF1
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorPrecision
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorRecall
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestralPrecision
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestralRecall
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFn
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFp
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFpr
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecision
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecisionCommonEdges
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecall
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecallCommonEdges
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTn
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTp
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeTrue
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.BicDiff
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.BicDiffPerRecord
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.BicEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.BicTrue
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedFP
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedLatentPrecision
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedPrecision
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedRecall
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedTP
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedTrue
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalseNegativeBidirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalsePositiveBidirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorTruePositiveBidirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonMeasuredAncestorRecallBidirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.CorrectSkeleton
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathPrecision
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathRecall
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.DensityEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.DensityTrue
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ElapsedCpuTime
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.F1Adj
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.F1All
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.F1Arrow
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.FalseNegativesAdjacencies
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.FalsePositiveAdjacencies
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.FBetaAdj
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderAlternative
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderNull
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.GraphExactlyRight
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaAverageSquaredDistance
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMaxSquaredDiffEstTrue
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMinSquaredDiffEstTrue
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgSquaredDifference
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaMaximumSquaredDifference
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaMinimumSquaredDifference
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst2
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedOrientationRatioEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliesLegalMag
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.KnowledgeSatisfied
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalseNegativeBidirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalsePositiveBidirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorRecallBidirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorTruePositiveBidirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.LegalPag
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.LocalGraphPrecision
This method returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.LocalGraphRecall
 
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MagCgScore
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MagDgScore
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MagSemScore
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPasses
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPassesBestOf10
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingP
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingPBestOf10
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialP
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialPBestOf10
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffP
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffPBestOf10
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPasses
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPassesBestOf10
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrAdj
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrArrow
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.Maximal
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.MaximalityCondition
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NoAlmostCyclicPathsCondition
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NoCyclicPathsCondition
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesPrecision
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesRecall
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NonancestorPrecision
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NonancestorRecall
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedF1
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedPrecision
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedRecall
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumAmbiguousTriples
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsNotInUnshieldedCollidersEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberCollidersEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInCollidersEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInUnshieldedCollidersEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesTrue
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesTrue
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberTailsEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberUnshieldedCollidersEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedBothNonancestorAncestor
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesTrue
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredDD
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredNL
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredPD
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredPL
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCommonMeasuredAncestorBidirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDefiniteDirectedEdgeAncestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeConfounded
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeNonAncestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleEdges
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeAncestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeNonAncestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleVisibleNonancestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectBidirected
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectDDAncestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectPDAncestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectVisibleEdges
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCoveringAdjacenciesInPag
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyDirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyNotDirectedPaths
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeAncestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeBnaMeasuredCounfounded
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNoMeasureAncestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNotAncNotRev
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeReversed
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdges
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsTrue
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedShouldBePartiallyDirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumEdgeInEstInTrue
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumGenuineAdjacenciesInPag
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectDDAncestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectPDAncestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectVisibleAncestors
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumLatentCommonAncestorBidirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumNondirectedEdges
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumParametersEst
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumPartiallyOrientedEdges
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumPossiblyDirected
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumUndirectedEdges
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdgeEst
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdges
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdgeTrue
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.OrientationPrecision
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.OrientationRecall
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyPrecision
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyRecall
Retrieves the abbreviation for the given statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ParameterColumn
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.PercentAmbiguous
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.PercentBidirectedEdges
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedEst
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedTrue
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.PvalueDistanceToAlpha
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.PvalueUniformityUnderNull
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPathF1
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPrecision
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedRecall
Retrieves the abbreviation for the SemidirectedRecall statistic.
getAbbreviation() - Method in interface edu.cmu.tetrad.algcomparison.statistic.Statistic
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.StructuralHammingDistance
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TailPrecision
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TailRecall
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesArrows
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesTails
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveArrow
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveTails
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionArrow
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionTails
Returns the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallArrows
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallTails
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveArrow
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveDirectedPathNonancestor
Retrieves the abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveTails
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalseNegative
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalsePositive
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCyclePrecision
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleRecall
The abbreviation for the statistic.
getAbbreviation() - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleTruePositive
The abbreviation for the statistic.
getAbsTotalEffects(Node, Node) - Method in class edu.cmu.tetrad.search.Ida
This method calculates the absolute total effects of node x on node y.
getAcyclicTrimmedBHat(Matrix) - Method in class edu.cmu.tetrad.search.IcaLingam
Calculates and returns the trimmed BHat matrix in an acyclic form using the given matrix W.
getAdjacencies() - Method in class edu.cmu.tetrad.search.Cpc
Returns the edges in the search graph as a set of undirected edges.
getAdjacencies() - Method in class edu.cmu.tetrad.search.Pc
Returns The edges of the searched graph.
getAdjacencies() - Method in class edu.cmu.tetrad.search.Pcd
Returns the set of adjacent edges in the graph.
getAdjacencies() - Method in class edu.cmu.tetrad.search.SvarFges
Retrieves the adjacency graph.
getAdjacencies() - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Getter for the field adjacencies.
getAdjacencies() - Method in class edu.cmu.tetrad.search.utils.PcCommon
Returns The edges in the search graph.
getAdjacencies() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns a list of adjacent node pairs in the current graph.
getAdjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Retrieves the preset adjacencies graph.
getAdjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
getAdjacencies.
getAdjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
getAdjacencies.
getAdjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
getAdjacencies.
getAdjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
getAdjacencies.
getAdjacentNodes(Node) - Method in class edu.cmu.tetrad.graph.Dag
Retrieves the adjacent nodes of a given node in the graph.
getAdjacentNodes(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getAdjacentNodes.
getAdjacentNodes(Node) - Method in interface edu.cmu.tetrad.graph.Graph
getAdjacentNodes.
getAdjacentNodes(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getAdjacentNodes.
getAdjacentNodes(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getAdjacentNodes.
getAdjacentNodes(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves a list of adjacent nodes for the given node.
getAdjacentNodes(Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns the nodes adjacent to v.
getAdjCor() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the adjacency correct.
getAdjFn() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the adjacency false negatives.
getAdjFp() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the adjacency false positives.
getAdjPrec() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the adjaency precision.
getAdjPrecision() - Method in class edu.cmu.tetrad.simulation.PRAOerrors
getAdjPrecision.
getAdjRec() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the adjacency recall.
getAdjRecall() - Method in class edu.cmu.tetrad.simulation.PRAOerrors
getAdjRecall.
getAhdCor() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the arrowhead correct.
getAhdFn() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the arrowhead false negatives.
getAhdFp() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the arrowhead false positives.
getAhdPrec() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the arrowhead precision.
getAhdRec() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the arrowhead recall.
getAlgorithm() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field algorithm.
getAlgorithmDescriptions() - Static method in enum class edu.cmu.tetrad.search.utils.BpcAlgorithmType
Returns the algorithm descriptions.
getAlgorithmName() - Method in class edu.cmu.tetrad.search.GrowShrink
Returns "Grow Shrink".
getAlgorithmName() - Method in interface edu.cmu.tetrad.search.IMbSearch
The name of the algorithm.
getAlgorithmName() - Method in class edu.cmu.tetrad.search.PcMb
Returns "PC-MB."
getAlgorithmName() - Method in class edu.cmu.tetrad.search.work_in_progress.Iamb
getAlgorithmName.
getAlgorithmName() - Method in class edu.cmu.tetrad.search.work_in_progress.IambnPc
getAlgorithmName.
getAlgorithmName() - Method in class edu.cmu.tetrad.search.work_in_progress.InterIamb
getAlgorithmName.
getAlgorithmName() - Method in class edu.cmu.tetrad.search.work_in_progress.Mmmb
getAlgorithmName.
getAlgorithmParameters(Algorithm) - Static method in class edu.cmu.tetrad.util.Params
getAlgorithmParameters.
getAlgorithms() - Method in class edu.cmu.tetrad.algcomparison.algorithm.Algorithms
Returns the list of algorithm.
getAllAttributes() - Method in class edu.cmu.tetrad.data.ContinuousVariable
getAllAttributes.
getAllAttributes() - Method in class edu.cmu.tetrad.data.DiscreteVariable
getAllAttributes.
getAllAttributes() - Method in class edu.cmu.tetrad.graph.Dag
getAllAttributes.
getAllAttributes() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getAllAttributes.
getAllAttributes() - Method in interface edu.cmu.tetrad.graph.Graph
getAllAttributes.
getAllAttributes() - Method in class edu.cmu.tetrad.graph.GraphNode
getAllAttributes.
getAllAttributes() - Method in class edu.cmu.tetrad.graph.LagGraph
getAllAttributes.
getAllAttributes() - Method in interface edu.cmu.tetrad.graph.Node
getAllAttributes.
getAllAttributes() - Method in class edu.cmu.tetrad.graph.SemGraph
getAllAttributes.
getAllAttributes() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves all the attributes stored in the object.
getAllGraphsByDirectingUndirectedEdges(Graph) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Returns a list of all possible graphs obtained by directing undirected edges in the given graph.
getAllowedColliders() - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
The Set of Triples representing the allowed colliders for the FciOrientDataExaminationStrategy.
getAllParents(Graph, Set<Node>) - Static method in class edu.cmu.tetrad.simulation.HsimUtils
getAllParents.
getAllRows(int) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Returns a list of rows 1...sampleSize.
getAllSubsetsIndependenceFacts() - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the set of independence facts used in the Markov check, for dseparation and dconnection separately.
getAlpha() - Method in class edu.cmu.tetrad.regression.LogisticRegression
Getter for the field alpha.
getAlpha() - Method in interface edu.cmu.tetrad.search.IndependenceTest
Returns the significance level of the independence test.
getAlpha() - Method in class edu.cmu.tetrad.search.IndTestIod
 
getAlpha() - Method in class edu.cmu.tetrad.search.test.ChiSquareTest
Returns the model significance level being used for tests.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Returns the alpha significance level of the test.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalCorrelation
Returns the model significance level.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Returns the significance level of the independence test.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Returns the significance level of the independence test.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Gets the model significance level.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
This method returns the alpha significance cutoff value used in the independence test.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Gets the getModel significance level.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Gets the getModel significance level.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Gets the getModel significance level.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
Returns the alpha value used for checking independence.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestMulti
Gets the getModel significance level.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestMvpLrt
Returns the significance level of the independence test.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Returns the alpha parameter for the probabilistic test.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestRegression
Gets the getModel significance level.
getAlpha() - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Gets the model significance level.
getAlpha() - Method in class edu.cmu.tetrad.search.test.Kci
Returns the significance level of the independence test.
getAlpha() - Method in class edu.cmu.tetrad.search.test.MsepTest
Returns an alpha level, 0.5.
getAlpha() - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Returns the significance level of the independence test.
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
Getter for the field alpha.
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
Getter for the field alpha.
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Getter for the field alpha.
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Gets the getModel significance level.
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Gets the getModel significance level.
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
 
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMnlrLr
Returns the significance level of the independence test.
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
Retrieves the significance level of the independence test.
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Retrieves the alpha level of the Independence Test.
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
getAlpha.
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Gets the getModel significance level.
getAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
Returns the significance level of the independence test.
getAlpha() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field alpha.
getAlpha() - Method in class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
Getter for the field alpha.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.graph.Dag
Returns a set of ambiguous triples.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Getter for the field ambiguousTriples.
getAmbiguousTriples() - Method in interface edu.cmu.tetrad.graph.Graph
getAmbiguousTriples.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.graph.LagGraph
Getter for the field ambiguousTriples.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.graph.SemGraph
Getter for the field ambiguousTriples.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves the set of ambiguous triples.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.graph.Underlines
Getter for the field ambiguousTriples.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.search.Cfci
Returns the ambiguous triples found in the search.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.search.Cpc
Returns the set of ambiguous triples found during the most recent run of the algorithm.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.search.PcMb
Returns the set of triples identified as ambiguous by the CPC algorithm during the most recent search.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.search.utils.PcCommon
Getter for the field ambiguousTriples.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Getter for the field ambiguousTriples.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Getter for the field ambiguousTriples.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Getter for the field ambiguousTriples.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Getter for the field ambiguousTriples.
getAmbiguousTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Getter for the field ambiguousTriples.
getAmbiguousTriples(Node) - Method in class edu.cmu.tetrad.search.Fas
Retrieves the list of ambiguous triples involving the given node.
getAmbiguousTriples(Node) - Method in class edu.cmu.tetrad.search.Fasd
Retrieves a list of ambiguous triples for the given node.
getAmbiguousTriples(Node) - Method in interface edu.cmu.tetrad.search.IFas
Returns the list of ambiguous triples found for a given node.
getAmbiguousTriples(Node) - Method in class edu.cmu.tetrad.search.SvarFas
Retrieves the list of ambiguous triples involving the given node.
getAmbiguousTriples(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.FasFdr
Returns the list of ambiguous triples found for a given node.
getAmbiguousTriplesFromGraph(Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Retrieves the list of ambiguous triples from the given graph for a given node.
getAncestors(Node) - Method in class edu.cmu.tetrad.graph.Paths
Retrieves the ancestors of a specified `Node` in the graph.
getAncestors(Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
getAncestors.
getAncestors(List<Node>) - Method in class edu.cmu.tetrad.graph.Paths
Returns a list of all ancestors of the given nodes.
getAncestorsMap() - Method in class edu.cmu.tetrad.graph.Paths
Return a map from each node to its collection of ancestors.
getAndersonDarlingA2(boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the Anderson-Darling A^2 statistic for the given list of results.
getAndersonDarlingA2(List<IndependenceResult>) - Method in class edu.cmu.tetrad.search.MarkovCheck
Calculates the Anderson-Darling A2 value for a list of independence results.
getAndersonDarlingA2Star(boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the Anderson-Darling A^2* statistic for the given list of results.
getAndersonDarlingP(boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the Anderson-Darling p-value for the given list of results.
getAndersonDarlingPValue(List<IndependenceResult>) - Method in class edu.cmu.tetrad.search.MarkovCheck
Calculates the Anderson-Darling p-value for a given list of independence results.
getAndersonDarlingTestAcceptsRejectsNodesForAllNodes(IndependenceTest, Graph, Double, Double) - Method in class edu.cmu.tetrad.search.MarkovCheck
Calculates the Anderson-Darling test and classifies nodes as accepted or rejected based on the given threshold.
getAndersonDarlingTestAcceptsRejectsNodesForAllNodesPlotData(IndependenceTest, Graph, Graph, Double, Double, Double) - Method in class edu.cmu.tetrad.search.MarkovCheck
Get accepts and rejects nodes for all nodes from Anderson-Darling test and generate the plot data for confusion statistics.
getAndersonDarlingTestAcceptsRejectsNodesForAllNodesPlotData2(IndependenceTest, Graph, Graph, Double, Double, Double) - Method in class edu.cmu.tetrad.search.MarkovCheck
Get accepts and rejects nodes for all nodes from Anderson-Darling test and generate the plot data for confusion statistics.
getAnnotatedClasses() - Method in class edu.cmu.tetrad.annotation.AbstractAnnotations
Get annotated classes.
getAnnotatedClasses(String, Class<T>) - Static method in class edu.cmu.tetrad.annotation.AnnotatedClassUtils
Gets a list of annotated classes in the given package.
getApacheData() - Method in class edu.cmu.tetrad.util.Matrix
Getter for the field apacheData.
getApparentlyNonadjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.VcFas
Getter for the field apparentlyNonadjacencies.
getApparentNonadjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
getApparentNonadjacencies.
getApparentNonadjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
getApparentNonadjacencies.
getApparentNonadjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
getApparentNonadjacencies.
getApparentNonadjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
getApparentNonadjacencies.
getArea(Function, double, double, int) - Static method in class edu.cmu.tetrad.util.Integrator
Finds the area under function f between x1 and x2 using Simpson's rule.
getArgument(int) - Method in interface edu.cmu.tetrad.calculator.expression.ExpressionSignature
getArgument.
getArrowsFn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.TailConfusion
getArrowsFn.
getArrowsFp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.TailConfusion
getArrowsFp.
getArrowsTn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.TailConfusion
getArrowsTn.
getArrowsTp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.TailConfusion
getArrowsTp.
getASquared() - Method in class edu.cmu.tetrad.data.AndersonDarlingTest
Constructs an Anderson-Darling test for the given column of data.
getASquared() - Method in class edu.cmu.tetrad.data.GeneralAndersonDarlingTest
Getter for the field aSquared.
getASquared() - Method in class edu.cmu.tetrad.data.MultiGeneralAndersonDarlingTest
Getter for the field aSquared.
getaSquaredStar() - Method in class edu.cmu.tetrad.sem.GeneralizedSemEstimator
Returns the value of the field aSquaredStar.
getASquaredStar() - Method in class edu.cmu.tetrad.data.AndersonDarlingTest
Constructs an Anderson-Darling test for the given column of data.
getASquaredStar() - Method in class edu.cmu.tetrad.data.GeneralAndersonDarlingTest
Getter for the field aSquaredStar.
getASquaredStar() - Method in class edu.cmu.tetrad.data.MultiGeneralAndersonDarlingTest
Getter for the field aSquaredStar.
getAssociatedNode(Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns the associated node for the given error node in the specified graph.
getAttribute(String) - Method in class edu.cmu.tetrad.data.ContinuousVariable
getAttribute.
getAttribute(String) - Method in class edu.cmu.tetrad.data.DiscreteVariable
getAttribute.
getAttribute(String) - Method in class edu.cmu.tetrad.graph.Dag
Retrieves the value associated with the given key in the attribute map.
getAttribute(String) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getAttribute.
getAttribute(String) - Method in interface edu.cmu.tetrad.graph.Graph
getAttribute.
getAttribute(String) - Method in class edu.cmu.tetrad.graph.GraphNode
getAttribute.
getAttribute(String) - Method in class edu.cmu.tetrad.graph.LagGraph
getAttribute.
getAttribute(String) - Method in interface edu.cmu.tetrad.graph.Node
getAttribute.
getAttribute(String) - Method in class edu.cmu.tetrad.graph.SemGraph
getAttribute.
getAttribute(String) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves the value associated with the specified key from the attributes map.
getAuc() - Method in class edu.cmu.tetrad.util.RocCalculator
Calculates the area under the ROC curve using a very clever Ramsey idea.
getAverageSquaredDistance(List<OrderedPair<Node>>) - Method in class edu.cmu.tetrad.search.IdaCheck
Returns the average of the squared distances between the true total effects and the IDA effect ranges the list of node pairs indicated.
getAvgMaxSquaredDiffEstTrue(List<OrderedPair<Node>>) - Method in class edu.cmu.tetrad.search.IdaCheck
Returns the average of the squared differences between the maximum total effects and the true total effects for the list of node pairs indicated.
getAvgMinSquaredDiffEstTrue(List<OrderedPair<Node>>) - Method in class edu.cmu.tetrad.search.IdaCheck
Returns the average of the squared differences between the minimum total effects and the true total effects for the list of node pairs indicated.
getB() - Method in class edu.cmu.tetrad.search.FaskOrig
Returns the coefficient matrix for the search.
getB() - Method in class edu.cmu.tetrad.search.utils.Bes.Arrow
Returns the second node.
getB() - Method in class edu.cmu.tetrad.sem.ParameterPair
Method getNumObjects
getB() - Method in class edu.cmu.tetrad.util.ChoiceGenerator
Getter for the field b.
getB() - Method in class edu.cmu.tetrad.util.dist.Split
Getter for the field b.
getBandwidth() - Method in interface edu.cmu.tetrad.search.utils.Kernel
Gets kernel bandwidth
getBandwidth() - Method in class edu.cmu.tetrad.search.utils.KernelGaussian
getBandwidth.
getBasalExpression() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Getter for the field basalExpression.
getBayesIm() - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
Getter for the field bayesIm.
getBayesIm() - Method in interface edu.cmu.tetrad.bayes.BayesUpdater
Returns the evidence for the updater.
getBayesIm() - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
Getter for the field bayesIm.
getBayesIm() - Method in class edu.cmu.tetrad.bayes.Identifiability
The BayesIm that this updater bases its update on.
getBayesIm() - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Returns the evidence for the updater.
getBayesIm() - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
The BayesIm that this updater bases its update on.
getBayesIm() - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Returns the Bayes IM being used.
getBayesIm(Element) - Method in class edu.cmu.tetrad.bayes.BayesXmlParser
Returns the BayesIm object represented by the given element.
getBayesIm(Element) - Method in class edu.cmu.tetrad.search.utils.BayesImParser
Takes an xml representation of a Bayes IM and reinstantiates the IM.
getBayesImObs() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Getter for the field bayesImObs.
getBayesIms() - Method in class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Returns the list of Bayes IMs.
getBayesImVars() - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Returns the variables of the BayesIM.
getBayesPm() - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the underlying Bayes PM.
getBayesPm() - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Getter for the field bayesPm.
getBayesPm() - Method in class edu.cmu.tetrad.bayes.EmBayesProperties
Getter for the field bayesPm.
getBayesPm() - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Getter for the field bayesPm.
getBayesPm() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Getter for the field bayesPm.
getBayesPm() - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
getBayesPm.
getBeta() - Method in class edu.cmu.tetrad.algcomparison.statistic.FBetaAdj
Getter for the field beta.
getBeta() - Method in class edu.pitt.csb.mgm.Mgm.MGMParams
Returns beta.
getBhat() - Method in class edu.cmu.tetrad.sem.Ricf.RicfResult
Returns the bhat matrix.
getBHat() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingam
Retrieves the bHat matrix.
getBic() - Method in class edu.cmu.tetrad.bayes.BayesProperties
Call after calling getLikelihoodP().
getBic() - Method in class edu.cmu.tetrad.bayes.EmBayesProperties
Calculates the BIC (Bayes Information Criterion) score for a BayesPM with respect to a given discrete data set.
getBic() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Returns the BIC score for this test.
getBic() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Score
getBic.
getBic() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.Score
Returns the BIC.
getBics() - Method in class edu.cmu.tetrad.search.Boss
Returns the BIC scores.
getBicScore() - Method in class edu.cmu.tetrad.sem.DagScorer
getBicScore.
getBicScore() - Method in interface edu.cmu.tetrad.sem.ISemIm
getBicScore.
getBicScore() - Method in interface edu.cmu.tetrad.sem.Scorer
getBicScore.
getBicScore() - Method in class edu.cmu.tetrad.sem.SemIm
getBicScore.
getBinomialPValue(boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the Binomial p-value for the given list of results.
getBinomialPValue(List<IndependenceResult>) - Method in class edu.cmu.tetrad.search.MarkovCheck
Calculates the binomial p-value based on the list of visible pairs.
getBMap(Graph) - Static method in class edu.cmu.tetrad.search.utils.AlmostCycleRemover
Returns a map of nodes to bidirected edges for them.
getBoolean(String) - Method in class edu.cmu.tetrad.util.Parameters
Returns the boolean value of the given parameter, looking up its default in the ParamDescriptions map.
getBoolean(String, boolean) - Method in class edu.cmu.tetrad.util.Parameters
Returns the boolean value of the given parameter, using the given default.
getBooleanInfluenceRate() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Getter for the field booleanInfluenceRate.
getBootstrapGraphs() - Method in class edu.cmu.tetrad.algcomparison.algorithm.AbstractBootstrapAlgorithm
Returns the bootstrap graphs.
getBootstrapGraphs() - Method in interface edu.cmu.tetrad.algcomparison.algorithm.ReturnsBootstrapGraphs
Returns the bootstrap graphs.
getBootstrappingParameters(Algorithm) - Static method in class edu.cmu.tetrad.util.Params
getBootstrappingParameters.
getBootstrapSample(DataSet, int) - Static method in class edu.cmu.tetrad.data.DataTransforms
getBootstrapSample.
getBootstrapSample(DataSet, int, RandomGenerator) - Static method in class edu.cmu.tetrad.data.DataTransforms
Get dataset sampled with replacement.
getBootstrapSample(Matrix, int) - Static method in class edu.cmu.tetrad.data.DataTransforms
getBootstrapSample.
getBreakpoints() - Method in class edu.cmu.tetrad.data.ContinuousDiscretizationSpec
Retrieves the array of breakpoints used for discretization.
getBreakpoints() - Method in class edu.cmu.tetrad.data.SplitCasesSpec
Getter for the field breakpoints.
getBscD() - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Returns the BSC-D score.
getBscI() - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Returns the BSC-I score.
getBump() - Method in class edu.cmu.tetrad.search.utils.Bes.Arrow
Returns the bump.
getC() - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
Getter for the field c.
getCases() - Method in class edu.cmu.tetrad.search.work_in_progress.MixtureModel
Getter for the field cases.
getCategories() - Method in class edu.cmu.tetrad.data.ContinuousDiscretizationSpec
Retrieves the list of categories for the discretized data.
getCategories() - Method in class edu.cmu.tetrad.data.DiscreteDiscretizationSpec
Getter for the field categories.
getCategories() - Method in class edu.cmu.tetrad.data.DiscreteVariable
Getter for the field categories.
getCategory(int) - Method in class edu.cmu.tetrad.data.DiscreteVariable
getCategory.
getCategory(Node, int) - Method in class edu.cmu.tetrad.bayes.BayesPm
Returns the index'th value for the given node.
getCategory(Node, int) - Method in class edu.cmu.tetrad.bayes.Evidence
getCategory.
getCategoryIndex(Node, String) - Method in class edu.cmu.tetrad.bayes.BayesPm
Returns the index of the given category for the given node.
getCategoryIndex(String, String) - Method in class edu.cmu.tetrad.bayes.Evidence
getCategoryIndex.
getCategoryIndex(String, String) - Method in class edu.cmu.tetrad.bayes.Proposition
getCategoryIndex.
getCauseNode() - Method in class edu.cmu.tetrad.search.Cstar.Record
Returns the cause node associated with this record.
getCell(int) - Method in class edu.cmu.tetrad.search.utils.AdTree
Returns the cell in the table for the given index.
getCellIndex(int...) - Method in class edu.cmu.tetrad.search.utils.AdTree
Returns the index of the cell in the table for the given coordinates.
getCellIndex(int[]) - Method in class edu.cmu.tetrad.util.MultiDimIntTable
Returns the index in the table for the cell with the given coordinates.
getCellNumber() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
While the simulate() method is being executed, returns the cell number of the cell currently being simulated in a particular dish, zero indexed.
getCellProb(int[]) - Method in class edu.cmu.tetrad.bayes.BayesImProbs
Calculates the probability in the given cell from the conditional probabilities in the BayesIm.
getCellProb(int[]) - Method in class edu.cmu.tetrad.bayes.CellTableProbs
Calculates the probability of a cell corresponding to the given variable values.
getCellProb(int[]) - Method in class edu.cmu.tetrad.bayes.DataSetProbs
getCellProb.
getCellProb(int[]) - Method in class edu.cmu.tetrad.bayes.DirichletDataSetProbs
getCellProb.
getCellProb(int[]) - Method in class edu.cmu.tetrad.bayes.IntAveDataSetProbs
getCellProb.
getCellProb(int[]) - Method in class edu.cmu.tetrad.bayes.StoredCellProbs
getCellProb.
getCellProb(int[]) - Method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
getCellProb.
getCenteringFrame() - Static method in class edu.cmu.tetrad.util.JOptionUtils
getCenteringFrame.
getCenterX() - Method in class edu.cmu.tetrad.data.ContinuousVariable
Getter for the field centerX.
getCenterX() - Method in class edu.cmu.tetrad.data.DiscreteVariable
Getter for the field centerX.
getCenterX() - Method in class edu.cmu.tetrad.graph.GraphNode
Getter for the field centerX.
getCenterX() - Method in interface edu.cmu.tetrad.graph.Node
Returns the x coordinate of the center of this node.
getCenterY() - Method in class edu.cmu.tetrad.data.ContinuousVariable
Getter for the field centerY.
getCenterY() - Method in class edu.cmu.tetrad.data.DiscreteVariable
Getter for the field centerY.
getCenterY() - Method in class edu.cmu.tetrad.graph.GraphNode
Getter for the field centerY.
getCenterY() - Method in interface edu.cmu.tetrad.graph.Node
Returns the y coordinate of the center of this node.
getCfi() - Method in interface edu.cmu.tetrad.sem.ISemIm
getCfi.
getCfi() - Method in class edu.cmu.tetrad.sem.SemIm
getCfi.
getChangedEdges() - Method in class edu.cmu.tetrad.search.utils.MeekRules
Returns a complete set of all the edges that were changed in the course of orientation, as a map from the previous edges in the graph to the new, changed edges for the same node pair.
getChildren(int) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns the children of a node v.
getChildren(Node) - Method in class edu.cmu.tetrad.graph.Dag
Retrieves the children of a specified Node in the graph.
getChildren(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getChildren.
getChildren(Node) - Method in interface edu.cmu.tetrad.graph.Graph
getChildren.
getChildren(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getChildren.
getChildren(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getChildren.
getChildren(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns a list of children nodes for the given node.
getChildren(Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns the children of a node v.
getChipChipVariability() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the chip to chip variability.
getChipChipVariability() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getChipChipVariability.
getChisq() - Method in class edu.cmu.tetrad.bayes.BayesProperties
Call after calling getLikelihoodP().
getChiSquare() - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Returns the chi Square value.
getChiSquare() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Score
getChiSquare.
getChiSquare() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.Score
Returns the chi square.
getChiSquare() - Method in class edu.cmu.tetrad.sem.DagScorer
getChiSquare.
getChiSquare() - Method in interface edu.cmu.tetrad.sem.ISemIm
getChiSquare.
getChiSquare() - Method in interface edu.cmu.tetrad.sem.Scorer
getChiSquare.
getChiSquare() - Method in class edu.cmu.tetrad.sem.SemIm
getChiSquare.
getClassifications() - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Returns the classification for the target variable.
getCliques(Node[], Graph) - Static method in class edu.cmu.tetrad.bayes.GraphTools
Get cliques in a decomposable graph.
getCliqueTree(Node[], Map<Node, Set<Node>>, Map<Node, Set<Node>>) - Static method in class edu.cmu.tetrad.bayes.GraphTools
getCliqueTree.
getCluster(int) - Method in class edu.cmu.tetrad.cluster.KMeans
getCluster.
getCluster(int) - Method in class edu.cmu.tetrad.data.Clusters
getCluster.
getClustering() - Method in class edu.cmu.tetrad.search.Mimbuild
Returns the clustering of measured variables, each of which is explained by a single latent.
getClustering() - Method in class edu.cmu.tetrad.search.MimbuildTrek
The clustering used.
getClusterName(int) - Method in class edu.cmu.tetrad.data.Clusters
getClusterName.
getClusters() - Method in interface edu.cmu.tetrad.cluster.ClusteringAlgorithm
getClusters.
getClusters() - Method in class edu.cmu.tetrad.cluster.KMeans
Getter for the field clusters.
getClusters() - Method in class edu.cmu.tetrad.data.Clusters
Getter for the field clusters.
getClusters() - Method in class edu.cmu.tetrad.search.Fofc
The clusters that are output by the algorithm from the last call to search().
getClusters() - Method in class edu.cmu.tetrad.search.Ftfc
Returns clusters output by the algorithm from the last call to search().
getCoef() - Method in class edu.cmu.tetrad.regression.RegressionResult
getCoef.
getCoef() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm.ParameterRange
Getter for the field coef.
getCoefficient() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialTerm
Returns the coefficient.
getCoefficientMatrix() - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
getCoefficientMatrix.
getCoefficientParameter(Node, Node) - Method in class edu.cmu.tetrad.sem.SemPm
getCoefficientParameter.
getCoefficientRange(Node, Node) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
getCoefficientRange.
getCoefs() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
The array of regression coefficients.
getCollapsedVarGraph() - Method in class edu.cmu.tetrad.search.utils.TsUtils.VarResult
Getter for the field collapsedVarGraph.
getColliderPath() - Method in class edu.cmu.tetrad.search.utils.DiscriminatingPath
Returns the collider subpath of the discriminating path.
getColliders() - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Return colliders
getCollidersFromGraph(Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
getCollidersFromGraph.
getColliderTriples() - Method in class edu.cmu.tetrad.search.utils.PcCommon
Getter for the field colliderTriples.
getColliderTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Getter for the field colliderTriples.
getColliderTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Getter for the field colliderTriples.
getColliderTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Getter for the field colliderTriples.
getColliderTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Getter for the field colliderTriples.
getColliderTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Getter for the field colliderTriples.
getColPerm() - Method in class edu.cmu.tetrad.search.utils.PermutationMatrixPair
Getter for the field colPerm.
getColumn(int) - Method in class edu.cmu.tetrad.util.Matrix
getColumn.
getColumn(Node) - Method in class edu.cmu.tetrad.data.BoxDataSet
getColumn.
getColumn(Node) - Method in interface edu.cmu.tetrad.data.DataSet
getColumn.
getColumn(Node) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getColumn.
getColumnToTooltip() - Method in class edu.cmu.tetrad.data.BoxDataSet
Getter for the field columnToTooltip.
getColumnToTooltip() - Method in interface edu.cmu.tetrad.data.DataSet
Returns the map of column names to tooltips.
getColumnToTooltip() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Getter for the field columnToTooltip.
getComparisonGraph() - Method in class edu.cmu.tetrad.algcomparison.Comparison
Returns the ComparisonGraph instance.
getComparisonGraph() - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
The type of graph the results are compared to.
getComparisonGraph(Graph) - Method in interface edu.cmu.tetrad.algcomparison.algorithm.Algorithm
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Bpc
Returns the comparison graph for the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Fofc
This method returns a comparison graph that is obtained from the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Ftfc
Retrieves the comparison graph for the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Dagma
Retrieves the comparison graph for the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.DirectLingam
Returns a comparison graph based on the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Returns a comparison graph based on the true directed graph, if there is one.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Returns a comparison graph based on the true directed graph, if there is one.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingam
Returns a comparison graph based on the true directed graph, if there is one.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingD
Retrieves the comparison graph of the provided true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.FirstInflection
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.mixed.Mgm
Returns the comparison graph for the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskLofsConcatenated
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FasLofs
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Returns a comparison graph based on the true directed graph, if there is one.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Boss
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossLingam
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cpc
Retrieves the comparison graph for the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fas
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMb
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMeasurement
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pc
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pcd
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMb
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.RestrictedBoss
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.SingleGraphAlg
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Sp
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Retrieves the comparison graph generated by applying the DAG-to-PAG transformation to the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossDumb
Retrieves a comparison graph by transforming a true directed graph into a partially directed graph (PAG).
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPag
Retrieves a comparison graph by transforming a true directed graph into a partially directed graph (PAG).
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Ccd
Retrieves the comparison graph for the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci
Retrieves the comparison graph by converting the given true directed graph into a partially directed graph (PAG) using the DAG to PAG transformation.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci
Returns the comparison graph based on the true directed graph, if there is one.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax
Returns the comparison graph transformed from the true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Retrieves the comparison graph by transforming the true directed graph (if there is one) into a partially directed acyclic graph (PAG).
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Retrieves a comparison graph by transforming a true directed graph into a partially directed graph (PAG).
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
Retrieves a comparison graph by transforming a true directed graph into a partially directed graph (PAG).
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci
Returns the comparison graph based on the true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci
Returns a comparison graph based on the provided true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.RfciBsc
Retrieves the comparison graph from the true directed graph, if there is one.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Returns the comparison graph created by converting a true directed graph into a partially directed acyclic graph (PAG).
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarFci
Returns a comparison graph based on the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Returns a comparison graph based on the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.other.FactorAnalysis
Returns an undirected graph used for comparison.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.other.Glasso
Retrieves a comparison graph for the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Eb
Returns a comparison graph based on the true directed graph, if there is one.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.FaskPw
Returns a comparison graph based on the provided true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R1
Returns a comparison graph based on the provided true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R2
Returns a comparison graph for the given true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R3
Generates a comparison graph based on the provided true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Rskew
Returns a comparison graph based on the true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.RskewE
Returns a comparison graph based on the provided true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Skew
Returns a comparison graph based on the true directed graph, if there is one.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.SkewE
Returns a comparison graph based on the provided true directed graph.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Tanh
Returns a comparison graph for the given true directed graph, if there is one.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection
Returns that graph that the result should be compared to.
getComparisonGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.algorithm.StARS
Returns that graph that the result should be compared to.
getComparisonGraph(Graph, Parameters) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns a comparison graph based on the specified parameters.
getConditionalProb(Proposition, Proposition) - Method in class edu.cmu.tetrad.bayes.BayesImProbs
Calculates the conditional probability of an assertion given a condition.
getConditionalProb(Proposition, Proposition) - Method in class edu.cmu.tetrad.bayes.CellTableProbs
Calculates the conditional probability of an assertion given a condition.
getConditionalProb(Proposition, Proposition) - Method in class edu.cmu.tetrad.bayes.DataSetProbs
Calculates the conditional probability of an assertion given a condition in a Bayes information model (Bayes IM).
getConditionalProb(Proposition, Proposition) - Method in class edu.cmu.tetrad.bayes.DirichletDataSetProbs
Calculates the conditional probability of an assertion given a condition in the context of a Bayes IM.
getConditionalProb(Proposition, Proposition) - Method in class edu.cmu.tetrad.bayes.IntAveDataSetProbs
Calculates the conditional probability of an assertion given a condition.
getConditionalProb(Proposition, Proposition) - Method in class edu.cmu.tetrad.bayes.StoredCellProbs
Calculates the conditional probability of an assertion given a condition.
getConditionalProb(Proposition, Proposition) - Method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
Calculates the conditional probability of an assertion given a condition.
getConditionalProbabilities(int[], int[], int[], int[]) - Method in class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
Get the joint probability of the nodes given their parents.
getConditionalProbabilities(int, int[], int[]) - Method in class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
Get the conditional probability of a node for all of its values.
getConditionalProbability(int, int, int[], int[]) - Method in class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
getConditionalProbability.
getConditioningNodes() - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the nodes that are possible Z1,...,Zn for X _||_ Y | Z1,...,Zn.
getConditions() - Method in class edu.cmu.tetrad.search.utils.PossibleMConnectingPath
Getter for the field conditions.
getConnectivity() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
getConnectivity.
getConnectivity() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
getConnectivity.
getConnectivity() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Returns (a copy of) the sorted map from factors to lagged factors which internally encodes the update graph.
getConnectivity() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Returns (a copy of) the sorted map from factors to lagged factors which internally encodes the update graph.
getConstantColumns(DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
getConstantColumns.
getContinousData(DataSet) - Static method in class edu.pitt.csb.mgm.MixedUtils
getContinousData.
getContinuousData() - Method in class edu.cmu.tetrad.data.MixedDataBox
Getter for the field continuousData.
getContinuousData(String) - Method in class edu.cmu.tetrad.data.Histogram
A convenience method to return the data for a particular named continuous variable.
getContinuousDataSet(DataModel) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
Returns the datamodel case to DataSet if it is continuous.
getContinuousInds(List<Node>) - Static method in class edu.pitt.csb.mgm.MixedUtils
getContinuousInds.
getCoordinates(int) - Method in class edu.cmu.tetrad.util.MultiDimIntTable
Returns the array representing the combination of parent values for this row.
getCorrectResult() - Method in class edu.cmu.tetrad.study.performance.ComparisonResult
Getter for the field correctResult.
getCorrelationMatrix() - Method in class edu.cmu.tetrad.data.BoxDataSet
getCorrelationMatrix.
getCorrelationMatrix() - Method in interface edu.cmu.tetrad.data.DataSet
If this is a continuous data set, returns the correlation matrix.
getCorrelationMatrix() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getCorrelationMatrix.
getCorrelationMatrix(DataSet) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
getCorrelationMatrix.
getCorrespondingNodeIndex(int, BayesIm) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the index of the given node in the given BayesIm.
getCorrespondingNodeIndex(int, BayesIm) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the index of the given node in the given BayesIm.
getCorrespondingNodeIndex(int, BayesIm) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Returns the corresponding node index in the given BayesIm based on the node index in this BayesIm.
getCorrespondingNodeIndex(int, BayesIm) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the index of the given node in the given BayesIm.
getCorrespondingNodeIndex(int, BayesIm) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the index of the given node in the given BayesIm.
getCount(int) - Method in class edu.cmu.tetrad.search.utils.AdTree
Returns the count of the cell in the table for the given index.
getCount(int[]) - Method in class edu.cmu.tetrad.search.utils.AdTree
Returns the count of the cell in the table for the given coordinates.
getCounts() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the counts.
getCov() - Method in interface edu.cmu.tetrad.search.IndependenceTest
Returns the covariance matrix.
getCov() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Returns the correlation matrix being analyzed.
getCov() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
Returns the covariance matrix for the data sets.
getCov() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Returns the covariance matrix of the concatenated data.
getCov() - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Returns the covariance matrix.
getCov() - Method in class edu.cmu.tetrad.search.test.Kci
Returns the covariance matrix.
getCov() - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Returns the covariance matrix.
getCov() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Retrieves the covariance matrix.
getCov() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
getCov.
getCov() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
getCov.
getCov() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
getCov.
getCov() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
getCov.
getCov(List<Integer>, int[], int[], DataSet, Matrix) - Static method in class edu.cmu.tetrad.search.score.SemBicScore
Computes the covariance matrix for the given subset of rows and columns in the provided data set.
getCovAndCoefs(int, int[], Matrix, ICovarianceMatrix, boolean, boolean) - Static method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the covariance matrix of the regression of the ith variable on its parents and the regression coefficients.
getCovAndCoefs(int, int[], Matrix, ICovarianceMatrix, boolean, List<Integer>) - Static method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the covariance matrix of the regression of the ith variable on its parents and the regression
getCovarianceMatrix() - Method in class edu.cmu.tetrad.data.BoxDataSet
getCovarianceMatrix.
getCovarianceMatrix() - Method in interface edu.cmu.tetrad.data.DataSet
If this is a continuous data set, returns the covariance matrix.
getCovarianceMatrix() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getCovarianceMatrix.
getCovarianceMatrix() - Method in class edu.cmu.tetrad.search.Bpc
Returns the wrapped covariance matrix.
getCovarianceMatrix() - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Retrieves the current covariance matrix object used by the IGFci algorithm.
getCovarianceMatrix(DataModel, boolean) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
Returns the model cast to ICovarianceMatrix if already a covariance matric, or else returns the covariance matrix for a dataset.
getCovarianceMatrix(DataSet, boolean) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
getCovarianceMatrix.
getCovarianceParameter(Node, Node) - Method in class edu.cmu.tetrad.sem.SemPm
getCovarianceParameter.
getCovarianceRange(Node, Node) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
getCovarianceRange.
getCovariances() - Method in class edu.cmu.tetrad.search.score.GicScores
Returns the sample size.
getCovariances() - Method in class edu.cmu.tetrad.search.score.PoissonPriorScore
Returns the covariance matrix.
getCovariances() - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the covariance matrix.
getCovariances() - Method in class edu.cmu.tetrad.search.score.ZsbScore
Returns the covariance matrix.
getCovariances() - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Getter for the field covariances.
getCovMatrix() - Method in interface edu.cmu.tetrad.search.utils.TetradTest
getCovMatrix.
getCovMatrix() - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
getCovMatrix.
getCovMatrix() - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
getCovMatrix.
getCovMatrix() - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
getCovMatrix.
getCovMatrix() - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Retrieves the current covariance matrix object used by the IGFci algorithm.
getCovMatrix() - Method in class edu.cmu.tetrad.sem.DagScorer
Getter for the field covMatrix.
getCovMatrix() - Method in interface edu.cmu.tetrad.sem.Scorer
getCovMatrix.
getCovMatrix() - Method in class edu.cmu.tetrad.sem.SemEstimator
Getter for the field covMatrix.
getCpcTripleType(Node, Node, Node, IndependenceTest, int, Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
getCpcTripleType.
getCpdag() - Method in class edu.cmu.tetrad.search.Dagma
Retrieves the value of the cpdag field.
getCpdag() - Method in class edu.cmu.tetrad.search.PermutationSearch
Retrieves the value of cpdag.
getCptMapType() - Method in interface edu.cmu.tetrad.bayes.BayesIm
Retrieves the CptMapType for this instance.
getCptMapType() - Method in class edu.cmu.tetrad.bayes.MlBayesIm
A flag indicating whether to use CptMaps or not.
getCurrentOffset() - Method in class edu.cmu.tetrad.calculator.parser.ExpressionLexer
Getter for the field currentOffset.
getCutoff(Function, double, double, double) - Static method in class edu.cmu.tetrad.util.CutoffFinder
Assumes f is a positive symmetric function between x1 and x2 about 0.
getD() - Method in class edu.pitt.csb.mgm.EigenDecomposition
Gets the block diagonal matrix D of the decomposition.
getDag() - Method in interface edu.cmu.tetrad.bayes.BayesIm
$Description
getDag() - Method in class edu.cmu.tetrad.bayes.BayesPm
Returns the DAG.
getDag() - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
getDag.
getDag() - Method in class edu.cmu.tetrad.bayes.MlBayesIm
getDag.
getDag() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
getDag.
getDag() - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
getDag.
getDag() - Method in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Returns the parent matrix for the graph.
getDag() - Method in class edu.cmu.tetrad.search.score.GraphScore
Returns a copy of the DAG being searched over.
getDag() - Method in class edu.cmu.tetrad.search.utils.DagSepsets
Returns the DAG being analyzed.
getDag() - Method in class edu.cmu.tetrad.search.utils.SepsetsGreedy
Retrieves the Directed Acyclic Graph (DAG) produced by the Sepsets algorithm.
getDag() - Method in class edu.cmu.tetrad.search.utils.SepsetsMaxP
Retrieves the Directed Acyclic Graph (DAG) produced by the Sepset algorithm.
getDag() - Method in class edu.cmu.tetrad.search.utils.SepsetsMinP
Retrieves the Directed Acyclic Graph (DAG) produced by the Sepsets algorithm.
getDag(Graph) - Method in class edu.cmu.tetrad.util.PagCache
Returns the Directed Acyclic Graph (DAG) corresponding to the given graph if it is a PAG that has previously been converted from a DAG.
getDag(List<Node>) - Method in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Returns the parent matrix for the graph.
getDag(List<Node>, Graph, boolean) - Static method in class edu.cmu.tetrad.graph.Paths
Generates a directed acyclic graph (DAG) based on the given list of nodes using Raskutti and Uhler's method.
getDagsInCpdagMeek(Graph, Knowledge) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Retrieves a list of directed acyclic graphs (DAGs) within the given completed partially directed acyclic graph (CPDAG) using the Meek rules.
getData() - Method in class edu.cmu.tetrad.data.Discretizer.Discretization
Retrieves the data associated with the discretization.
getData() - Method in class edu.cmu.tetrad.data.DoubleDataBox
Getter for the field data.
getData() - Method in class edu.cmu.tetrad.data.IntDataBox
Getter for the field data.
getData() - Method in class edu.cmu.tetrad.data.TimeSeriesData
getData.
getData() - Method in class edu.cmu.tetrad.search.CompositeIndependenceTest
getData.
getData() - Method in interface edu.cmu.tetrad.search.IndependenceTest
getData.
getData() - Method in class edu.cmu.tetrad.search.IndTestIod
 
getData() - Method in class edu.cmu.tetrad.search.score.PoissonPriorScore
Returns the data set.
getData() - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the data model.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Returns the data being analyzed.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalCorrelation
Returns the data set being analyzed.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Returns the data.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Returns the dataset being analyzed.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Returns the data set being analyzed.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
Returns the concatenated data.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Returns the concatenated data.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Returns the data.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Returns the data set being analyzed.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
Returns the facts supplied in the constructor, which constutite a data model.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestMulti
Retrieves the data set.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestMvpLrt
Returns the data.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Returns the data model associated with this instance.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestRegression
Returns the data used.
getData() - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Gets the data set used for the independence test.
getData() - Method in class edu.cmu.tetrad.search.test.Kci
Returns The data model for the independence test.
getData() - Method in class edu.cmu.tetrad.search.test.MsepTest
Returns the data set used for the test.
getData() - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Retrieves the data model associated with this object.
getData() - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Getter for the field data.
getData() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Retrieves the dataset used in the independence test.
getData() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Retrieves the data set from the method.
getData() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
getData.
getData() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
Returne the original data for the method.
getData() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMnlrLr
Returns the dataset.
getData() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
Retrieves the original data used for the independence test.
getData() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Retrieve the data set used in the independence test.
getData() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
getData.
getData() - Method in class edu.cmu.tetrad.search.work_in_progress.MixtureModel
Getter for the field data.
getData() - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
getData.
getData() - Method in class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
Retrieves the original dataset used for the independence test.
getDataBox() - Method in class edu.cmu.tetrad.data.BoxDataSet
Getter for the field dataBox.
getDataFile() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field dataFile.
getDataModel() - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the data model.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Returns the data model at the specified index.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.NLSemSimulation
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Returns the data model at the specified index.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
Returns the number of data sets to simulate.
getDataModel(int) - Method in interface edu.cmu.tetrad.algcomparison.simulation.Simulation
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.SingleDatasetSimulation
Retrieves the data model at the specified index from this simulation.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs
Returns the number of data sets to simulate.
getDataModel(int) - Method in class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
Returns the number of data sets to simulate.
getDataSet() - Method in class edu.cmu.tetrad.bayes.CellTableProbs
Getter for the field dataSet.
getDataSet() - Method in class edu.cmu.tetrad.bayes.DataSetProbs
Getter for the field dataSet.
getDataSet() - Method in class edu.cmu.tetrad.bayes.DirichletDataSetProbs
Getter for the field dataSet.
getDataSet() - Method in class edu.cmu.tetrad.bayes.FactoredBayesStructuralEM
Getter for the field dataSet.
getDataSet() - Method in class edu.cmu.tetrad.bayes.IntAveDataSetProbs
Getter for the field dataSet.
getDataSet() - Method in class edu.cmu.tetrad.data.Histogram
Getter for the field dataSet.
getDataSet() - Method in class edu.cmu.tetrad.search.score.BdeScore
Returns the DataSet associated with this method.
getDataSet() - Method in class edu.cmu.tetrad.search.score.BdeuScore
Retrieves the dataset associated with this BdeuScore object.
getDataSet() - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
Returns the dataset.
getDataSet() - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
Returns the dataset.
getDataSet() - Method in interface edu.cmu.tetrad.search.score.DiscreteScore
Returns the dataset.
getDataSet() - Method in class edu.cmu.tetrad.search.score.GicScores
Returns the dataset.
getDataSet() - Method in class edu.cmu.tetrad.search.score.IndTestScore
Returns the data set.
getDataSet() - Method in interface edu.cmu.tetrad.search.utils.TetradTest
getDataSet.
getDataSet() - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
Getter for the field dataSet.
getDataSet() - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
Getter for the field dataSet.
getDataSet() - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
getDataSet.
getDataSet() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Retrieves a DataSet object.
getDataSet() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Retrieves the data set from the current context.
getDataSet() - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Retrieves the dataset used in the scoring calculations.
getDataSet() - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
getDataSet.
getDataSet() - Method in class edu.cmu.tetrad.sem.DagScorer
Getter for the field dataSet.
getDataSet() - Method in interface edu.cmu.tetrad.sem.Scorer
getDataSet.
getDataSet() - Method in class edu.cmu.tetrad.sem.SemEstimator
Getter for the field dataSet.
getDataSet() - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbs
Getter for the field dataSet.
getDataSets() - Method in interface edu.cmu.tetrad.search.IndependenceTest
Returns the datasets for this test
getDataSets() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Returns the (singleton) list of datasets being analyzed.
getDataSets() - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Returns the data sets used for the independence test.
getDataSets() - Method in class edu.cmu.tetrad.search.test.Kci
Returns a list consisting of the dataset for this test.
getDataSets() - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
 
getDataSets() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Retrieves the list of data sets.
getDataSets() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Returns the datasets for this test
getDataSets() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Retrieves the data sets used in the independence test.
getDataType() - Method in interface edu.cmu.tetrad.algcomparison.algorithm.Algorithm
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Bpc
Retrieves the data type of the algorithm's output.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Fofc
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Ftfc
Returns the type of the data set that the search algorithm requires.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Dagma
Retrieves the data type of the algorithm's output.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.DirectLingam
Returns the data type of the algorithm, which can be Continuous, Discrete, Mixed, Graph, Covariance, or All.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Retrieves the data type of the dataset.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Retrieves the data type of the dataset.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingam
Returns the data type of the given method.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingD
Retrieves the data type of the algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.FirstInflection
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.mixed.Mgm
Retrieves the data type required by the search algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskLofsConcatenated
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FasLofs
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Returns the type of the data set.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Boss
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossLingam
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cpc
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fas
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMb
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMeasurement
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pc
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pcd
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMb
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.RestrictedBoss
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.SingleGraphAlg
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Sp
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Retrieves the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossDumb
Retrieves the data type required by the search algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPag
Retrieves the data type required by the search algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Ccd
Retrieves the data type that the search requires.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci
Retrieves the data type required by the search algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Retrieves the data type required for the search algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Retrieves the data type required by the search algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
Retrieves the data type required by the search algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci
Retrieves the data type associated with the method.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.RfciBsc
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarFci
Retrieves the data type required by the search algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Returns the data type that this method requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.other.FactorAnalysis
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.other.Glasso
Retrieves the data type required by the search algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Eb
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.FaskPw
Retrieves the data type of the dataset.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R1
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R2
Returns the data type required for the search, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R3
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Rskew
Retrieves the data type required by the algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.RskewE
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Skew
Retrieves the data type of the current algorithm.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.SkewE
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Tanh
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.algorithm.StARS
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.BasisFunctionBicTest
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.BdeuTest
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.CciTest
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.ChiSquare
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.ConditionalGaussianLRT
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.DegenerateGaussianLRT
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.DiscreteBicTest
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.FisherZ
Retrieves the data type of the independence test.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.GICScoreTests
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.GSquare
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in interface edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.Kci
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.MagSemBicTest
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.Mnlrlrt
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.MSeparationTest
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.MultinomialLogisticRegressionWald
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.Mvplrt
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.PoissonPriorTest
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.PositiveCorr
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.ProbabilisticTest
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.SemBicDTest
Retrieves the data type of the test dataset.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.independence.SemBicTest
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.BasisFunctionBicScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.BdeuScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.ConditionalGaussianBicScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.DegenerateGaussianBicScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.DiscreteBicScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.EbicScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.FisherZScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.GicScores
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.MagDgBicScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.MSeparationScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.MVPBicScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.PoissonPriorScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.PositiveCorrScore
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in interface edu.cmu.tetrad.algcomparison.score.ScoreWrapper
Returns the data type that the search requires, whether continuous, discrete, or mixed.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.SemBicScore
Returns the data type of the current score.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.SemBicScoreDeterministic
Retrieves the data type of the ScoreWrapper implementation.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.score.ZhangShenBoundScore
Returns the data type of the score.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Returns the data type of the data set.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.NLSemSimulation
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Returns the data type of the data set.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
Returns the data type of the data.
getDataType() - Method in interface edu.cmu.tetrad.algcomparison.simulation.Simulation
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.SingleDatasetSimulation
Retrieves the data type of the data set.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
Returns the data type of the data.
getDataType() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field dataType.
getDatum(int, int) - Method in class edu.cmu.tetrad.data.TimeSeriesData
getDatum.
getDecayRate() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Getter for the field decayRate.
getDefaultValue() - Method in class edu.cmu.tetrad.util.ParamDescription
Getter for the field defaultValue.
getDefiniteNonadjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
getDefiniteNonadjacencies.
getDefiniteNonadjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
getDefiniteNonadjacencies.
getDefiniteNonadjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
getDefiniteNonadjacencies.
getDefiniteNonadjacencies() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
getDefiniteNonadjacencies.
getDegree() - Method in class edu.cmu.tetrad.graph.Dag
getDegree.
getDegree() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getDegree.
getDegree() - Method in interface edu.cmu.tetrad.graph.Graph
getDegree.
getDegree() - Method in class edu.cmu.tetrad.graph.LagGraph
getDegree.
getDegree() - Method in class edu.cmu.tetrad.graph.SemGraph
getDegree.
getDegree() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns the degree of the graph.
getDegree(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns the maximum degree of a graph.
getDegree(Node) - Method in class edu.cmu.tetrad.graph.Dag
Returns the degree of a given node in the graph.
getDegree(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getDegree.
getDegree(Node) - Method in interface edu.cmu.tetrad.graph.Graph
getDegree.
getDegree(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getDegree.
getDegree(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getDegree.
getDegree(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves the degree of a given node in the graph.
getDemixedData() - Method in class edu.cmu.tetrad.search.work_in_progress.MixtureModel
getDemixedData.
getDepth() - Method in class edu.cmu.tetrad.search.Cpc
Returns the depth of the search--that is, the maximum number of variables conditioned on in any conditional independence test.
getDepth() - Method in class edu.cmu.tetrad.search.FaskOrig
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.Pc
Returns the current depth of search--that is, the maximum number of conditioning nodes for any conditional independence checked.
getDepth() - Method in class edu.cmu.tetrad.search.Pcd
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.PcMb
Returns the depth of the search--that is, the maximum number of variables conditioned on in any conditional independence test.
getDepth() - Method in class edu.cmu.tetrad.search.SvarFci
Returns the depth of search--i.e., the maximum number of conditioning variables for tests.
getDepth() - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.utils.PcCommon
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.utils.PossibleMsepFci
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyScoreBased
Retrieves the depth value of the FciOrientDataExaminationStrategyScoreBased object.
getDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.Dci
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.FasDci
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.FasLofs
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.Mmhc
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.VcFas
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Getter for the field depth.
getDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Getter for the field depth.
getDescendants(Node) - Method in class edu.cmu.tetrad.graph.Paths
Returns a list of all descendants of the given node.
getDescendants(List<Node>) - Method in class edu.cmu.tetrad.graph.Paths
Retrieves the descendants of the given list of nodes.
getDescendantsMap() - Method in class edu.cmu.tetrad.graph.Paths
Return a map from each node to its collection of descendants.
getDescription() - Method in interface edu.cmu.tetrad.algcomparison.algorithm.Algorithm
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Bpc
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Fofc
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Ftfc
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Dagma
Returns the description of the DAGMA algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.DirectLingam
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Returns a short, one-line description of the FASK algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Returns a short, one-line description of the FASK algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingam
Returns the description of the ICA-LiNGAM algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingD
Retrieves the description of the algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.FirstInflection
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.mixed.Mgm
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskLofsConcatenated
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FasLofs
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Returns the description of this method.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Boss
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossLingam
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cpc
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fas
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMb
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMeasurement
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pc
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pcd
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMb
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.RestrictedBoss
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.SingleGraphAlg
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Sp
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Returns a description of the BFCI (Best-order FCI) algorithm using the description of its independence test and score.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossDumb
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPag
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Ccd
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci
Returns the description of the algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax
Returns a description of the algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Returns a description of the GFCI (Greedy Fast Causal Inference) algorithm using the description of the independence test and score associated with it.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci
Returns a description of the method.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.RfciBsc
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarFci
Returns the description of the method.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Returns a description of this method.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.other.FactorAnalysis
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.other.Glasso
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Eb
Returns a description of the algorithm's orientation method.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.FaskPw
Returns a description of the RSkew algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R1
Returns a description of this method.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R2
Returns the description of the algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R3
Returns a description of the method.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Rskew
Returns a description of the algorithm being used, including the initial graph if available.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.RskewE
Returns the description of the current algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Skew
Returns a description of the method.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.SkewE
Returns a description of the algorithm used.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Tanh
Returns a description of the method.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.algorithm.StARS
Returns a short, one-line description of this algorithm.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.graph.Cyclic
Returns a short, one-line description of this graph type.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.graph.ErdosRenyi
Returns a short, one-line description of this graph type.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.graph.RandomForward
Returns a short, one-line description of this graph type.
getDescription() - Method in interface edu.cmu.tetrad.algcomparison.graph.RandomGraph
Returns a short, one-line description of this graph type.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.graph.RandomSingleFactorMim
Returns a short, one-line description of this graph type.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.graph.RandomTwoFactorMim
Returns a short, one-line description of this graph type.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.graph.ScaleFree
Returns a short, one-line description of this graph type.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.graph.SingleGraph
Returns a short, one-line description of this graph type.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.BasisFunctionBicTest
Returns a short description of the test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.BdeuTest
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.CciTest
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.ChiSquare
Returns a short description of the Chi Square Test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.ConditionalGaussianLRT
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.DegenerateGaussianLRT
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.DiscreteBicTest
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.FisherZ
Retrieves the description of the Fisher Z test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.GICScoreTests
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.GSquare
Returns a short of this independence test.
getDescription() - Method in interface edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.Kci
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.MagSemBicTest
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.Mnlrlrt
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.MSeparationTest
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.MultinomialLogisticRegressionWald
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.Mvplrt
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.PoissonPriorTest
Returns a short description of the test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.PositiveCorr
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.ProbabilisticTest
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.SemBicDTest
Returns a short description of this IndependenceTest.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.independence.SemBicTest
Returns a short description of the test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.BasisFunctionBicScore
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.BdeuScore
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.ConditionalGaussianBicScore
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.DegenerateGaussianBicScore
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.DiscreteBicScore
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.EbicScore
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.FisherZScore
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.GicScores
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.MagDgBicScore
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.MSeparationScore
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.MVPBicScore
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.PoissonPriorScore
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.PositiveCorrScore
Returns a short of this independence test.
getDescription() - Method in interface edu.cmu.tetrad.algcomparison.score.ScoreWrapper
Returns a short of this independence test.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.SemBicScore
Returns the description of the Sem BIC Score.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.SemBicScoreDeterministic
Returns a short description of the method.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.score.ZhangShenBoundScore
Returns the description of the Zhang-Shen Bound Score.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1
getDescription.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.NLSemSimulation
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
Returns the description of the simulation.
getDescription() - Method in interface edu.cmu.tetrad.algcomparison.simulation.Simulation
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.SingleDatasetSimulation
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFn
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFp
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFpr
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTn
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTp
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTpr
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorF1
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestralPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestralRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFn
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFp
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFpr
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecisionCommonEdges
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecallCommonEdges
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTn
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTp
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.BicDiff
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.BicDiffPerRecord
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.BicEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.BicTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedFP
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedLatentPrecision
Returns a short description of the statistic, which is the percentage of bidirected edges for which a latent confounder exists.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedTP
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalseNegativeBidirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalsePositiveBidirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorTruePositiveBidirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonMeasuredAncestorRecallBidirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.CorrectSkeleton
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.DensityEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.DensityTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ElapsedCpuTime
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.F1Adj
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.F1All
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.F1Arrow
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.FalseNegativesAdjacencies
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.FalsePositiveAdjacencies
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.FBetaAdj
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderAlternative
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderNull
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.GraphExactlyRight
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaAverageSquaredDistance
Retrieves the description for this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMaxSquaredDiffEstTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMinSquaredDiffEstTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgSquaredDifference
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaMaximumSquaredDifference
Retrieves the description for this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaMinimumSquaredDifference
Retrieves the description for this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst
A Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst2
A Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedOrientationRatioEst
A Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliesLegalMag
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.KnowledgeSatisfied
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalseNegativeBidirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalsePositiveBidirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorRecallBidirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorTruePositiveBidirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.LegalPag
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.LocalGraphPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.LocalGraphRecall
 
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MagCgScore
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MagDgScore
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MagSemScore
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPasses
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPassesBestOf10
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingP
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingPBestOf10
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialP
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialPBestOf10
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffP
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffPBestOf10
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPasses
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPassesBestOf10
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrAdj
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrArrow
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.Maximal
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.MaximalityCondition
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NoAlmostCyclicPathsCondition
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NoCyclicPathsCondition
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NonancestorPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NonancestorRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedF1
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumAmbiguousTriples
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsNotInUnshieldedCollidersEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberCollidersEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInCollidersEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInUnshieldedCollidersEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberTailsEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberUnshieldedCollidersEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedBothNonancestorAncestor
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredDD
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredNL
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredPD
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredPL
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCommonMeasuredAncestorBidirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDefiniteDirectedEdgeAncestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeConfounded
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeNonAncestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleEdges
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeAncestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeNonAncestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleVisibleNonancestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectBidirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectDDAncestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectPDAncestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectVisibleEdges
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCoveringAdjacenciesInPag
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyDirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyNotDirectedPaths
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeAncestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeBnaMeasuredCounfounded
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNoMeasureAncestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNotAncNotRev
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeReversed
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdges
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedShouldBePartiallyDirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumEdgeInEstInTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumGenuineAdjacenciesInPag
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectDDAncestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectPDAncestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectVisibleAncestors
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumLatentCommonAncestorBidirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumNondirectedEdges
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumParametersEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumPartiallyOrientedEdges
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumPossiblyDirected
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumUndirectedEdges
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdgeEst
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdges
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdgeTrue
Retrieves the description of the statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.OrientationPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.OrientationRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ParameterColumn
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.PercentAmbiguous
Retrieves the description of the statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.PercentBidirectedEdges
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedEst
Retrieves the description of the statistic: Proportion of semi(X, Y) in estimated graph for which there is no semi(Y, X) in true graph.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedTrue
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.PvalueDistanceToAlpha
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.PvalueUniformityUnderNull
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPathF1
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedRecall
Returns a short one-line description of this statistic.
getDescription() - Method in interface edu.cmu.tetrad.algcomparison.statistic.Statistic
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.StructuralHammingDistance
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TailPrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TailRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesArrows
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesTails
Retrieves a short one-line description of the statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveArrow
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveTails
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionArrow
Retrieves the description of the statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionTails
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallArrows
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallTails
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveArrow
Retrieves a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveDirectedPathNonancestor
Retrieves the description of the statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveTails
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalseNegative
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalsePositive
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCyclePrecision
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleRecall
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleTruePositive
Returns a short one-line description of this statistic.
getDescription() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph
getDescription.
getDescription() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
getDescription.
getDescription() - Method in class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
Returns the description of the simulation.
getDescription() - Method in class edu.cmu.tetrad.util.DefaultTetradLoggerConfig.DefaultEvent
getDescription.
getDescription() - Method in interface edu.cmu.tetrad.util.TetradLoggerConfig.Event
Returns the description of the event.
getDescriptorFromToken(String) - Method in class edu.cmu.tetrad.calculator.expression.ExpressionManager
getDescriptorFromToken.
getDescriptors() - Method in class edu.cmu.tetrad.calculator.expression.ExpressionManager
Getter for the field descriptors.
getDeterminant() - Method in class edu.pitt.csb.mgm.EigenDecomposition
Computes the determinant of the matrix.
getDeterminismThreshold() - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Getter for the field determinismThreshold.
getDf() - Method in class edu.cmu.tetrad.search.test.ChiSquareTest.Result
Returns the adjusted degrees of freedom, or -1 if the degrees of freedom cannot be determined.
getDf() - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Returns the degrees of freedom associated with the most recent call of isIndependent.
getDim(int) - Method in class edu.cmu.tetrad.util.MultiDimIntTable
Returns the dimension of the given variable.
getDimension() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
getDimension.
getDimension() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
getDimension.
getDimension() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
getDimension.
getDimension() - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Retrieves the dimension of the covariance matrix.
getDimension(int) - Method in interface edu.cmu.tetrad.data.CellTable
Returns the dimension of the specified variable in the cell table.
getDimension(int) - Method in class edu.cmu.tetrad.data.CellTableAdTree
Returns the dimensions of the given variable.
getDimension(int) - Method in class edu.cmu.tetrad.data.CellTableCountSample
Returns the dimensions of the given variable.
getDimension(int) - Method in class edu.cmu.tetrad.util.MultiDimIntTable
Returns the dimension of the given variable.
getDir() - Method in class edu.cmu.tetrad.search.Cstar
getDir.
getDirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Returns the directed edge between the given nodes, if one exists in the graph.
getDirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getDirectedEdge.
getDirectedEdge(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
getDirectedEdge.
getDirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getDirectedEdge.
getDirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getDirectedEdge.
getDirectedEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves the directed edge connecting two nodes in the graph.
getDirectedEdgeHead(Edge) - Static method in class edu.cmu.tetrad.graph.Edges
For a directed edge, returns the node adjacent to the arrow endpoint.
getDirectedEdgeTail(Edge) - Static method in class edu.cmu.tetrad.graph.Edges
For a directed edge, returns the node adjacent to the null endpoint.
getDiscLevels(DataSet) - Static method in class edu.pitt.csb.mgm.MixedUtils
getDiscLevels.
getDiscreteData() - Method in class edu.cmu.tetrad.data.MixedDataBox
Getter for the field discreteData.
getDiscreteData(DataSet) - Static method in class edu.pitt.csb.mgm.MixedUtils
getDiscreteData.
getDiscreteDataSet(DataModel) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
Returns the datamodel case to DataSet if it is discrete.
getDiscreteInds(List<Node>) - Static method in class edu.pitt.csb.mgm.MixedUtils
getDiscreteInds.
getDiscreteScore() - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
getDiscreteScore.
getDishBumpStDev() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.DishModel
Getter for the field dishBumpStDev.
getDishDishVariability() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the standard deviation in percentage of random dish bump values away from 100%.
getDishDishVariability() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getDishDishVariability.
getDishModel() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Gets the dish model.
getDishNumber() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.DishModel
Returns the number of the getModel dish.
getDishNumber() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
While the simulate() method is being executed, returns the dish number of the cell currently being simulated, zero indexed.
getDisplayString(LaggedFactor) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.DisplayNameHandler
Converts the given lagged factor into a display string.
getDisplayString(String, int) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.DisplayNameHandler
Uses the given factor and lag information to construct a display string.
getDist() - Method in class edu.cmu.tetrad.sem.EmpiricalDistributionForExpression
getDist.
getDistalEndpoint(Node) - Method in class edu.cmu.tetrad.graph.Edge
getDistalEndpoint.
getDistalNode(Node) - Method in class edu.cmu.tetrad.graph.Edge
Traverses the edge in an undirected fashion--given one node along the edge, returns the node at the opposite end of the edge.
getDistances(Graph, double[][], DataSet, CpdagParentDistancesFromTrue.DistanceType) - Method in class edu.cmu.tetrad.search.CpdagParentDistancesFromTrue
Calculates the distance matrix for the edges in the given CPDAG (outputCpdag).
getDistribution() - Method in class edu.cmu.tetrad.sem.Parameter
Getter for the field distribution.
getDistribution(int) - Method in class edu.cmu.tetrad.search.work_in_progress.MixtureModel
Classifies a given case into a model, based on which model has the highest gamma value for that case.
getDmStructure() - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Getter for the field dmStructure.
getDof() - Method in class edu.cmu.tetrad.bayes.BayesProperties
Call after calling getLikelihoodP().
getDof() - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianLikelihood.Ret
Returns the degrees of freedom.
getDof() - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt.Ret
Returns the degrees of freedom.
getDof() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Score
getDof.
getDof() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.Score
Returns the degrees of freedom.
getDof() - Method in class edu.cmu.tetrad.sem.DagScorer
getDof.
getDof() - Method in interface edu.cmu.tetrad.sem.Scorer
getDof.
getDof() - Method in class edu.cmu.tetrad.sem.SemPm
getDof.
getDoF(int, int[]) - Method in class edu.cmu.tetrad.search.score.MvpLikelihood
Returns the score of the node at index i, given its parents.
getDoF(int, int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.MnlrLikelihood
Returns the degrees of freedom of a child given its parents.
getDottedUnderlinedTriplesFromGraph(Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Retrieves the list of dotted and underlined triples from the given graph, with the specified node as the middle node.
getDottedUnderlines() - Method in class edu.cmu.tetrad.graph.Dag
getDottedUnderlines.
getDottedUnderlines() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getDottedUnderlines.
getDottedUnderlines() - Method in interface edu.cmu.tetrad.graph.Graph
getDottedUnderlines.
getDottedUnderlines() - Method in class edu.cmu.tetrad.graph.LagGraph
getDottedUnderlines.
getDottedUnderlines() - Method in class edu.cmu.tetrad.graph.SemGraph
getDottedUnderlines.
getDottedUnderlines() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns a set of Triple objects representing dotted underlines.
getDottedUnderlines() - Method in class edu.cmu.tetrad.graph.Underlines
getDottedUnderlines.
getDouble(int, int) - Method in class edu.cmu.tetrad.data.BoxDataSet
getDouble.
getDouble(int, int) - Method in interface edu.cmu.tetrad.data.DataSet
getDouble.
getDouble(int, int) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getDouble.
getDouble(String) - Method in class edu.cmu.tetrad.util.Parameters
Returns the double value of the given parameter, looking up its default in the ParamDescriptions map.
getDouble(String, double) - Method in class edu.cmu.tetrad.util.Parameters
Returns the object value of the given parameter, using the given default.
getDoubleData() - Method in class edu.cmu.tetrad.data.BoxDataSet
getDoubleData.
getDoubleData() - Method in interface edu.cmu.tetrad.data.DataSet
getDoubleData.
getDoubleData() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getDoubleData.
getDoubleMissingValue() - Static method in class edu.cmu.tetrad.data.ContinuousVariable
getDoubleMissingValue.
getDoubleValue(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Returns the value stored at element (r,c) as a double
getDoubleValue(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrix
Returns the value stored at element (r,c) as a double
getDoubleValue(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrixF
Returns the value stored at element (r,c) as a double
getDoubleValue(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.Matrix
Returns the value stored at element (r,c) as a double
getDoubleValue(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.MatrixF
Returns the value stored at element (r,c) as a double
getEBICprior() - Method in class edu.cmu.tetrad.search.score.MvpLikelihood
getEBICprior.
getEBICprior() - Method in class edu.cmu.tetrad.search.work_in_progress.MnlrLikelihood
getEBICprior.
getEdge() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm.ParameterRange
Getter for the field edge.
getEdge(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Digraph
Returns the value of edge between nodes i and j
getEdge(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Returns the value of edge between nodes i and j
getEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Retrieves the edge between two nodes in the graph.
getEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getEdge.
getEdge(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
getEdge.
getEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getEdge.
getEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getEdge.
getEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves the edge between the given nodes.
getEdgeCoef() - Method in class edu.cmu.tetrad.sem.DagScorer
Getter for the field edgeCoef.
getEdgeCoef() - Method in interface edu.cmu.tetrad.sem.Scorer
getEdgeCoef.
getEdgeCoef() - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field edgeCoef.
getEdgeCoef(Edge) - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field edgeCoef.
getEdgeCoef(Node, Node) - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field edgeCoef.
getEdgeCoef(Node, Node) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
Getter for the field edgeCoef.
getEdgeParams(Node, Node, GeneralizedSemPm) - Static method in class edu.pitt.csb.mgm.MixedUtils
getEdgeParams.
getEdgeParams(String, String, GeneralizedSemPm) - Static method in class edu.pitt.csb.mgm.MixedUtils
getEdgeParams.
getEdges() - Method in class edu.cmu.tetrad.data.KnowledgeGroup
getEdges.
getEdges() - Method in class edu.cmu.tetrad.graph.Dag
getEdges.
getEdges() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getEdges.
getEdges() - Method in interface edu.cmu.tetrad.graph.Graph
getEdges.
getEdges() - Method in class edu.cmu.tetrad.graph.LagGraph
getEdges.
getEdges() - Method in class edu.cmu.tetrad.graph.SemGraph
getEdges.
getEdges() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves the set of edges in the graph.
getEdges() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns a list of edges for the current graph as a list of ordered pairs.
getEdges() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Digraph
Returns the edge matrix.
getEdges(Node) - Method in class edu.cmu.tetrad.graph.Dag
Returns a list of edges connected to the given node.
getEdges(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getEdges.
getEdges(Node) - Method in interface edu.cmu.tetrad.graph.Graph
getEdges.
getEdges(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getEdges.
getEdges(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getEdges.
getEdges(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns the list of edges connected to the specified node.
getEdges(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Returns a list of edges between the specified nodes in the graph.
getEdges(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getEdges.
getEdges(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
getEdges.
getEdges(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getEdges.
getEdges(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getEdges.
getEdges(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Finds all edges between two nodes.
getEdgesAdded() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the edges added.
getEdgesRemoved() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the edges removed.
getEdgeType() - Method in class edu.cmu.tetrad.graph.EdgeTypeProbability
Getter for the field edgeType.
getEdgeTypeProbabilities() - Method in class edu.cmu.tetrad.graph.Edge
Getter for the field edgeTypeProbabilities.
getEdgewiseComparisonString(Graph, Graph) - Static method in class edu.cmu.tetrad.algcomparison.CompareTwoGraphs
Returns an edgewise comparison of two graphs.
getEdgewiseComparisonString(String, Graph, String, Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
getEdgewiseComparisonString.
getEffectNode() - Method in class edu.cmu.tetrad.search.Cstar.Record
Retrieves the effect node of the record.
getEffects() - Method in class edu.cmu.tetrad.search.Ida.NodeEffects
Returns the effects.
getEigenvector(int) - Method in class edu.pitt.csb.mgm.EigenDecomposition
Gets a copy of the ith eigenvector of the original matrix.
getElapsed() - Method in class edu.cmu.tetrad.study.performance.ComparisonResult
Getter for the field elapsed.
getElapsedTime() - Method in class edu.cmu.tetrad.search.Cfci
Returns the elapsed time to the search.
getElapsedTime() - Method in class edu.cmu.tetrad.search.Cpc
Returns the elapsed time of search in milliseconds, after search() has been run.
getElapsedTime() - Method in class edu.cmu.tetrad.search.Fas
Returns the elapsed time of the search.
getElapsedTime() - Method in class edu.cmu.tetrad.search.Fasd
Returns the elapsed time of the method execution.
getElapsedTime() - Method in class edu.cmu.tetrad.search.FaskOrig
getElapsedTime.
getElapsedTime() - Method in class edu.cmu.tetrad.search.Fci
Returns the elapsed time of search.
getElapsedTime() - Method in class edu.cmu.tetrad.search.FciMax
Returns the elapsed time of search.
getElapsedTime() - Method in class edu.cmu.tetrad.search.Fges
Returns the elapsed time of the search.
getElapsedTime() - Method in class edu.cmu.tetrad.search.FgesMb
Returns the elapsed time of the search.
getElapsedTime() - Method in interface edu.cmu.tetrad.search.IFas
Returns the elapsed time of the search.
getElapsedTime() - Method in class edu.cmu.tetrad.search.Pc
Returns the elapsed time of the search, in milliseconds.
getElapsedTime() - Method in class edu.cmu.tetrad.search.Pcd
Returns the elapsed time in milliseconds since the start of the method.
getElapsedTime() - Method in class edu.cmu.tetrad.search.PcMb
Returns the elapsed time of the most recent search.
getElapsedTime() - Method in class edu.cmu.tetrad.search.Rfci
Returns the elapsed time of the search.
getElapsedTime() - Method in class edu.cmu.tetrad.search.SvarFas
 
getElapsedTime() - Method in class edu.cmu.tetrad.search.SvarFges
Returns the elapsed time of the search.
getElapsedTime() - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Getter for the field elapsedTime.
getElapsedTime() - Method in class edu.cmu.tetrad.search.utils.PcCommon
Getter for the field elapsedTime.
getElapsedTime() - Method in class edu.cmu.tetrad.search.work_in_progress.Dci
Getter for the field elapsedTime.
getElapsedTime() - Method in class edu.cmu.tetrad.search.work_in_progress.FasFdr
Returns the elapsed time of the search.
getElapsedTime() - Method in class edu.cmu.tetrad.search.work_in_progress.FasLofs
getElapsedTime.
getElapsedTime() - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Returns the elapsed time.
getElapsedTime() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Getter for the field elapsedTime.
getElapsedTime() - Method in class edu.cmu.tetrad.search.work_in_progress.Mmhc
getElapsedTime.
getElapsedTime() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Getter for the field elapsedTime.
getElapsedTime() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Getter for the field elapsedTime.
getElapsedTime() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Getter for the field elapsedTime.
getElapsedTime() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Getter for the field elapsedTime.
getElapsedTime() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Getter for the field elapsedTime.
getElapsedTime() - Method in class edu.pitt.csb.mgm.Mgm
Return time of execution for learning.
getElapsedTime(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.ExternalAlgorithm
getElapsedTime.
getElement(BayesIm) - Static method in class edu.cmu.tetrad.bayes.BayesXmlRenderer
Private constructor to prevent instantiation.
getElement(SemIm) - Static method in class edu.cmu.tetrad.sem.SemXmlRenderer
Converts a Sem Im into xml.
getEndpoint(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Returns the endpoint between two nodes in the graph.
getEndpoint(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getEndpoint.
getEndpoint(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
getEndpoint.
getEndpoint(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getEndpoint.
getEndpoint(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getEndpoint.
getEndpoint(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns the endpoint between two nodes in the graph.
getEndpoint1() - Method in class edu.cmu.tetrad.graph.Edge
Getter for the field endpoint1.
getEndpoint2() - Method in class edu.cmu.tetrad.graph.Edge
Getter for the field endpoint2.
getEqualFrequencyBreakPoints(double[], int) - Static method in class edu.cmu.tetrad.data.Discretizer
getEqualFrequencyBreakPoints.
getErrCovar() - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field errCovar.
getErrCovar(Node, Node) - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field errCovar.
getErrorCovar() - Method in class edu.cmu.tetrad.sem.DagScorer
Getter for the field errorCovar.
getErrorCovar() - Method in interface edu.cmu.tetrad.sem.Scorer
getErrorCovar.
getErrorCovariance(Node, Node) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
getErrorCovariance.
getErrorDistribution(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Returns the error distribution for the factor'th factor.
getErrorDistribution(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Returns the error distribution for the factor'th factor.
getErrorDistribution(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialFunction
Returns the error distribution for the factor'th factor.
getErrorNode(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getErrorNode.
getErrorNode(Node) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the error node associated with the given node.
getErrorNodes() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Returns the list of exogenous variableNodes.
getErrorNodes() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
getErrorNodes.
getErrorsTemplate() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Returns the error template string.
getErrorVariance(Node) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
getErrorVariance.
getErrVar(Node) - Method in class edu.cmu.tetrad.sem.SemIm
getErrVar.
getEss(ICovarianceMatrix) - Static method in class edu.cmu.tetrad.data.DataUtils
Returns the equivalent sample size, assuming all units are equally correlated and all unit variances are equal.
getEstimatedIm() - Method in class edu.cmu.tetrad.bayes.EmBayesEstimator
Getter for the field estimatedIm.
getEstimatedSem() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Score
getEstimatedSem.
getEstimatedSem() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.Score
Returns the estimated SEM IM.
getEstimatedSem() - Method in class edu.cmu.tetrad.sem.SemEstimator
Getter for the field estimatedSem.
getEstimatedSem() - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbs
Getter for the field estimatedSem.
getEstimator() - Method in class edu.cmu.tetrad.bayes.EmBayesProperties
Getter for the field estimator.
getEstSem() - Method in class edu.cmu.tetrad.sem.DagScorer
getEstSem.
getEstSem() - Method in interface edu.cmu.tetrad.sem.Scorer
getEstSem.
getEvidence() - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
Getter for the field evidence.
getEvidence() - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
Getter for the field evidence.
getEvidence() - Method in class edu.cmu.tetrad.bayes.Identifiability
Getter for the field evidence.
getEvidence() - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Returns the manipulation that was used to manipulate the Bayes IM.
getEvidence() - Method in interface edu.cmu.tetrad.bayes.ManipulatingBayesUpdater
Returns the manipulation that was used to manipulate the Bayes IM.
getEvidence() - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
Getter for the field evidence.
getEvidence() - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Getter for the field evidence.
getEvidence() - Method in class edu.cmu.tetrad.sem.SemUpdater
Getter for the field evidence.
getExampleNonsingular(ICovarianceMatrix, int) - Static method in class edu.cmu.tetrad.data.DataUtils
getExampleNonsingular.
getExogenous(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getExogenous.
getExpression() - Method in class edu.cmu.tetrad.calculator.expression.Equation
Getter for the field expression.
getExpressions() - Method in class edu.cmu.tetrad.calculator.expression.ConstantExpression
getExpressions.
getExpressions() - Method in class edu.cmu.tetrad.calculator.expression.EvaluationExpression
getExpressions.
getExpressions() - Method in interface edu.cmu.tetrad.calculator.expression.Expression
getExpressions.
getExpressions() - Method in class edu.cmu.tetrad.calculator.expression.VariableExpression
getExpressions.
getExternalGraph() - Method in class edu.cmu.tetrad.search.SvarFges
Getter for the field externalGraph.
getExternalGraph() - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Getter for the field externalGraph.
getFact() - Method in class edu.cmu.tetrad.search.test.IndependenceResult
Returns the independence fact being stored.
getFactor() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Returns the factor.
getFactor() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedEdge
Getter for the field factor.
getFactor() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedFactor
Returns the name of the lagged factor.
getFactor(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity
Returns the (string name of) the factor at the given index.
getFactor(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph
Returns the (string name of) the factor at the given index.
getFactors() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
getFactors.
getFactors() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
getFactors.
getFactors() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Returns a SortedSet of the factors in this graph.
getFactors() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Returns a SortedSet of the factors in this graph.
getFacts() - Method in class edu.cmu.tetrad.data.IndependenceFacts
getFacts.
getFilename() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.StoredLagGraphParams
Returns the stored file.
getFinalStrategyUsingDsep(Graph, Knowledge, boolean) - Static method in class edu.cmu.tetrad.search.utils.DagToPag
Returns the final strategy for finding a PAG using D-SEP.
getFirst() - Method in class edu.cmu.tetrad.graph.NodePair
Getter for the field first.
getFirst() - Method in class edu.cmu.tetrad.graph.OrderedPair
Getter for the field first.
getFirstEdge() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move
Getter for the field edge.
getFirstLayer() - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
getFirstLayer.
getFirstStepStored() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the index of the first step to actually be stored out.
getFirstStepStored() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getFirstStepStored.
getFixedParameters() - Method in interface edu.cmu.tetrad.sem.ISemIm
getFixedParameters.
getFixedParameters() - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field fixedParameters.
getFml() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Score
getFml.
getFml() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.Score
Returns the Fml.
getFml() - Method in class edu.cmu.tetrad.sem.DagScorer
The value of the maximum likelihood function for the getModel the model (Bollen 107).
getFml() - Method in interface edu.cmu.tetrad.sem.Scorer
getFml.
getFn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.AdjacencyConfusion
Returns the false negative count.
getFn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
False negatives.
getFn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.BidirectedConfusion
Returns the number of false negatives.
getFn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.LocalGraphConfusion
Returns the false negatives (FN) value of the LocalGraphConfusion object.
getFn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.OrientationConfusion
Getter for the field fn.
getFnc() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
False negatives for common edges.
getForbidden() - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
Getter for the field forbidden.
getFp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.AdjacencyConfusion
Returns the false positive count.
getFp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
False positives.
getFp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.BidirectedConfusion
Returns the number of false positives.
getFp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.LocalGraphConfusion
Retrieves the value of false positives (FP) from the LocalGraphConfusion object.
getFp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.OrientationConfusion
Getter for the field fp.
getFpc() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
False positives for common edges.
getFractionDependent(boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the fraction of dependent judgments for the given list of results.
getFractionDependent(List<IndependenceResult>) - Method in class edu.cmu.tetrad.search.MarkovCheck
Calculates the fraction of dependent results.
getFreeParameters() - Method in interface edu.cmu.tetrad.sem.ISemIm
getFreeParameters.
getFreeParameters() - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field freeParameters.
getFreeParameters() - Method in class edu.cmu.tetrad.sem.SemPm
getFreeParameters.
getFreeParamValues() - Method in interface edu.cmu.tetrad.sem.ISemIm
getFreeParamValues.
getFreeParamValues() - Method in class edu.cmu.tetrad.sem.SemIm
getFreeParamValues.
getFrequencies() - Method in class edu.cmu.tetrad.data.Histogram
getFrequencies.
getFrom() - Method in class edu.cmu.tetrad.data.KnowledgeEdge
Getter for the field from.
getFromVariables() - Method in class edu.cmu.tetrad.data.KnowledgeGroup
getFromVariables.
getFullGraph() - Method in class edu.cmu.tetrad.search.Mimbuild
The full graph inferred, including the edges from latents to measures.
getFullGraph() - Method in class edu.cmu.tetrad.search.MimbuildTrek
The full graph discovered.
getFullTierOrdering() - Method in class edu.cmu.tetrad.graph.SemGraph
getFullTierOrdering.
getFValue(int, double[][]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Calculates the new value for the F function, for the given factor, in light of the given history.
getGeneralizedSemPm() - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Retrieves the GeneralizedSemPm object associated with this GeneralizedSemIm.
getGesDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Getter for the field gesDepth.
getGraph() - Method in interface edu.cmu.tetrad.regression.Regression
getGraph.
getGraph() - Method in class edu.cmu.tetrad.regression.RegressionCovariance
Getter for the field graph.
getGraph() - Method in class edu.cmu.tetrad.regression.RegressionDataset
Getter for the field graph.
getGraph() - Method in class edu.cmu.tetrad.search.Cpc
The graph that's constructed during the search.
getGraph() - Method in class edu.cmu.tetrad.search.score.ScoredGraph
Returns the graph.
getGraph() - Method in class edu.cmu.tetrad.search.test.MsepTest
Returns the underlying graph that is being used to calculate d-separation relationships.
getGraph() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
Getter for the field graph.
getGraph() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
Getter for the field graph.
getGraph() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.GraphWithPValue
Getter for the field graph.
getGraph() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
The graph that's constructed during the search.
getGraph() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
The graph that's constructed during the search.
getGraph() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
The graph that's constructed during the search.
getGraph() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
The graph that's constructed during the search.
getGraph() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
The graph that's constructed during the search.
getGraph() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Returns the structural model graph this SEM PM is using.
getGraph() - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Getter for the field graph.
getGraph() - Method in class edu.cmu.tetrad.sem.SemPm
Getter for the field graph.
getGraph(boolean) - Method in class edu.cmu.tetrad.search.Grasp
Returns the graph implied by the discovered permutation.
getGraph(boolean) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns the DAG build for the current permutation, or its CPDAG.
getGraph(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
getGraph.
getGraph(List<Node>, Map<Node, Set<Node>>, boolean) - Static method in class edu.cmu.tetrad.search.PermutationSearch
Construct a graph given a specification of the parents for each node.
getGraph(List<Node>, Map<Node, Set<Node>>, Knowledge, boolean) - Static method in class edu.cmu.tetrad.search.PermutationSearch
Constructs a graph given a specification of the parents for each node.
getGraphComparison(Graph, Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Just counts arrowhead errors--for cyclic edges counts an arrowhead at each node.
getGraphFile() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field graphFile.
getGraphName() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.RevealOutputGraph
Getter for the field graphName.
getGraphName() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealOutputGraph
Getter for the field graphName.
getGraphName() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealOutputGraph
Getter for the field graphName.
getGraphName() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Returns the name of the graph
getGraphName() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.OutputGraph
Returns the name of the graph
getGraphNum() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field graphNum.
getGraphRBD() - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Returns the graph that was learned using the BSC-D method.
getGraphRBI() - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Returns the graph that was learned using the BSC-I method.
getGraphWithoutXToY(Graph, Node, Node, GraphUtils.GraphType) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns a graph that is obtained by removing the edge from node x to node y from the input graph.
getGST(Node) - Method in class edu.cmu.tetrad.search.PermutationSearch
Retrieves the GrowShrinkTree (GST) associated with the given Node.
getH() - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Returns a map from independence facts to their probabilities of independence.
getH() - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
getH.
getHigh() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm.ParameterRange
Getter for the field high.
getHighPValueAlpha() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
Getter for the field highPValueAlpha.
getHistory() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the history that was set in the constructor.
getHistoryArray() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Returns the getModel history array.
getI() - Method in class edu.cmu.tetrad.search.utils.Sextad
Getter for the field i.
getI() - Method in class edu.cmu.tetrad.search.utils.Tetrad
Getter for the field i.
getI() - Method in class edu.cmu.tetrad.search.work_in_progress.Sextad
Getter for the field i.
getId() - Method in class edu.cmu.tetrad.util.DefaultTetradLoggerConfig.DefaultEvent
getId.
getId() - Method in interface edu.cmu.tetrad.util.TetradLoggerConfig.Event
Returns the ID of the event.
getIdaMinEffect(Node, Node) - Method in class edu.cmu.tetrad.search.IdaCheck
Gets the signed minimum absolute total effect value between two nodes.
getImagEigenvalue(int) - Method in class edu.pitt.csb.mgm.EigenDecomposition
Gets the imaginary part of the ith eigenvalue of the original matrix.
getImagEigenvalues() - Method in class edu.pitt.csb.mgm.EigenDecomposition
Gets a copy of the imaginary parts of the eigenvalues of the original matrix.
getImplCovar() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
Getter for the field implCovar.
getImplCovar(boolean) - Method in interface edu.cmu.tetrad.sem.ISemIm
getImplCovar.
getImplCovar(boolean) - Method in class edu.cmu.tetrad.sem.SemIm
getImplCovar.
getImplCovar(List<Node>) - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field implCovar.
getImplCovarMeas() - Method in interface edu.cmu.tetrad.sem.ISemIm
getImplCovarMeas.
getImplCovarMeas() - Method in class edu.cmu.tetrad.sem.SemIm
getImplCovarMeas.
getImplCovarMeas() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
Getter for the field implCovarMeas.
getIms() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Retrieves the list of GeneralizedSemIm objects used for simulation.
getIms() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Retrieves the list of SemIm objects used for simulation.
getIndegree() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Getter for the field indegree.
getIndegree(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Calculates the maximum indegree in a given graph.
getIndegree(Node) - Method in class edu.cmu.tetrad.graph.Dag
Returns the indegree of the specified node in the graph.
getIndegree(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getIndegree.
getIndegree(Node) - Method in interface edu.cmu.tetrad.graph.Graph
getIndegree.
getIndegree(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getIndegree.
getIndegree(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getIndegree.
getIndegree(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns the indegree of a given node in the graph.
getIndegreeType() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Getter for the field indegreeType.
getIndependenceFacts() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Returns the independence facts in the form 1:2|3 for use in various Tetrad algorithms.
getIndependenceNodes() - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the nodes that are possible X and Y for X _||_ Y | Z1,...,Zn.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.BFci
The independence test being used for some steps in final orientation.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.Cpc
Rreturn the independence test used in the search, set in the constructor.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.Fci
Returns the independence test used in search.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.FciMax
Returns the independence test used in search.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.GFci
Returns the independence test used in search.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the independence test being used.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.Pc
Returns the independence test being used in the search.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.Pcd
Retrieves the IndependenceTest used by this method.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.Rfci
Returns the independence test.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.SpFci
Returns the independence test used in search.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.SvarFci
Returns independence test.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.utils.PcCommon
Getter for the field independenceTest.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Retrieves the current independence test object being used.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Getter for the field independenceTest.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.work_in_progress.Mmhc
Getter for the field independenceTest.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Getter for the field independenceTest.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Getter for the field independenceTest.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Getter for the field independenceTest.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Getter for the field independenceTest.
getIndependenceTest() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Getter for the field independenceTest.
getIndependenceTest() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field independenceTest.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Retrieves the IndependenceWrapper associated with this object.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Returns the independence wrapper.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Returns the independence wrapper.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Returns the independence wrapper.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cpc
Retrieves the IndependenceWrapper associated with this object.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Returns the independence wrapper.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fas
Returns the independence wrapper.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Returns the independence wrapper.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pc
Returns the independence wrapper.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMb
Returns the independence wrapper.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Returns the IndependenceWrapper associated with this Bfci algorithm.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Ccd
Returns the IndependenceWrapper object associated with this instance.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci
Retrieves the IndependenceWrapper used by the algorithm.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci
Retrieves the IndependenceWrapper object associated with this method.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax
Retrieves the IndependenceWrapper associated with the algorithm.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Returns the independence wrapper associated with this instance.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Retrieves the IndependenceWrapper object associated with this method.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
 
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci
Returns the independence wrapper.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Retrieves the IndependenceWrapper associated with this algorithm.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarFci
Retrieves the IndependenceWrapper object associated with this algorithm.
getIndependenceWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Retrieves the IndependenceWrapper object associated with this algorithm.
getIndependenceWrapper() - Method in interface edu.cmu.tetrad.algcomparison.utils.TakesIndependenceWrapper
Returns the independence wrapper.
getIndex() - Method in class edu.cmu.tetrad.search.utils.Bes.Arrow
Returns the index of the arrow.
getIndex() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch.Gene
getIndex.
getIndex() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedParent
Returns the index of the parent.
getIndex(int, IndexedParent) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity
Returns the index of the parent of the given factor that is equal to the given IndexedParent, or -1 if the given IndexedParent is not equal to any parent.
getIndex(int, IndexedParent) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph
Returns the index of the parent of the given factor that is equal to the given IndexedParent, or -1 if the given IndexedParent is not equal to any parent.
getIndex(DataModel) - Method in class edu.cmu.tetrad.algcomparison.algorithm.ExternalAlgorithm
getIndex.
getIndex(Endpoint) - Static method in class edu.cmu.tetrad.graph.MisclassificationUtils
getIndex.
getIndex(Node) - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
Getter for the field index.
getIndex(String) - Method in class edu.cmu.tetrad.data.DiscreteVariable
getIndex.
getIndex(String) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
getIndex.
getIndex(String) - Static method in class edu.cmu.tetrad.sem.LargeScaleSimulation
getIndex.
getIndex(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity
Returns the index of the given String factor.
getIndex(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph
Returns the index of the given String factor.
getIndex(String) - Static method in class edu.cmu.tetrad.study.performance.Comparison2
getIndex.
getIndex(String, LaggedFactor) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity
Returns the index of the given parent for the given factor.
getIndex(String, LaggedFactor) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph
Returns the index of the given parent for the given factor.
getIndexedLagGraph() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
getIndexedLagGraph.
getIndexedLagGraph() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Returns the indexed connectivity.
getIndexedLagGraph() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialFunction
Returns the indexed connectivity.
getIndexedLagGraph() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.UpdateFunction
getIndexedLagGraph.
getIndices() - Method in class edu.cmu.tetrad.util.IndexedMatrix
Getter for the field indices.
getInducingPath(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.graph.Paths
This method calculates the inducing path between two measured nodes in a graph.
getInhibitExcite() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Returns the inhibit/excite.
getInitialAllowedColliders() - Method in class edu.cmu.tetrad.search.utils.FciOrient
Returns the initial allowed colliders based on the current strategy.
getInitialAllowedColliders() - Method in interface edu.cmu.tetrad.search.utils.R0R4Strategy
Returns the allowed colliders for the current strategy.
getInitialAllowedColliders() - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Retrieves the initial set of allowed colliders.
getInitializer() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Returns the initializer.
getInitSync() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Determines whether initialization is synchronized.
getInputNodes() - Method in interface edu.cmu.tetrad.sem.ConnectionFunction
getInputNodes.
getInputs() - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Getter for the field inputs.
getInputs(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch.LatentStructure
getInputs.
getInstance() - Static method in class edu.cmu.tetrad.annotation.AlgorithmAnnotations
Gets the instance of this class.
getInstance() - Static method in class edu.cmu.tetrad.annotation.ScoreAnnotations
getInstance.
getInstance() - Static method in class edu.cmu.tetrad.annotation.TestOfIndependenceAnnotations
getInstance.
getInstance() - Static method in class edu.cmu.tetrad.calculator.expression.ExpressionManager
getInstance.
getInstance() - Static method in class edu.cmu.tetrad.sem.TemplateExpander
getInstance.
getInstance() - Static method in class edu.cmu.tetrad.util.AlgorithmDescriptions
Gets the instance of this class.
getInstance() - Static method in class edu.cmu.tetrad.util.IndependenceTestDescriptions
getInstance.
getInstance() - Static method in class edu.cmu.tetrad.util.LogUtils
getInstance.
getInstance() - Static method in class edu.cmu.tetrad.util.NumberFormatUtil
getInstance.
getInstance() - Static method in class edu.cmu.tetrad.util.PagCache
Returns the singleton instance of the PagCache.
getInstance() - Static method in class edu.cmu.tetrad.util.ParamDescriptions
getInstance.
getInstance() - Static method in class edu.cmu.tetrad.util.RandomUtil
getInstance.
getInstance() - Static method in class edu.cmu.tetrad.util.ScoreDescriptions
getInstance.
getInstance() - Static method in class edu.cmu.tetrad.util.TaskManager
Getter for the field instance.
getInstance() - Static method in class edu.cmu.tetrad.util.TetradLogger
Returns an instance of TetradLogger.
getInstance() - Static method in class edu.cmu.tetrad.util.TetradProperties
getInstance.
getInt(int, int) - Method in class edu.cmu.tetrad.data.BoxDataSet
getInt.
getInt(int, int) - Method in interface edu.cmu.tetrad.data.DataSet
getInt.
getInt(int, int) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getInt.
getInt(String) - Method in class edu.cmu.tetrad.util.Parameters
Returns the integer value of the given parameter, looking up its default in the ParamDescriptions map.
getInt(String, int) - Method in class edu.cmu.tetrad.util.Parameters
Returns the integer value of the given parameter, looking up its default in the ParamDescriptions map.
getIntegerDistribution(Context) - Method in class edu.cmu.tetrad.calculator.expression.ConstantExpression
getIntegerDistribution.
getIntegerDistribution(Context) - Method in class edu.cmu.tetrad.calculator.expression.EvaluationExpression
getIntegerDistribution.
getIntegerDistribution(Context) - Method in interface edu.cmu.tetrad.calculator.expression.Expression
getIntegerDistribution.
getIntegerDistribution(Context) - Method in class edu.cmu.tetrad.calculator.expression.VariableExpression
getIntegerDistribution.
getIntercept() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
The intercept.
getIntercept(Node) - Method in interface edu.cmu.tetrad.sem.ISemIm
getIntercept.
getIntercept(Node) - Method in class edu.cmu.tetrad.sem.SemIm
Calculates the intercept for a given node.
getIntersectionComparisonString(List<Graph>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Generates a comparison string for the intersection of multiple graphs.
getInterval() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets the interval (in time steps) between time steps stored out.
getInterval() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getInterval.
getInts(int[]) - Static method in class edu.cmu.tetrad.search.utils.ClusterSignificance
Converts a list of indices into a list of Integers representing a cluster.
getIterations() - Method in class edu.cmu.tetrad.search.work_in_progress.Ion
getIterations.
getIterations() - Method in class edu.cmu.tetrad.sem.Ricf.RicfResult
Returns the number of iterations.
getJ() - Method in class edu.cmu.tetrad.search.utils.Sextad
Getter for the field j.
getJ() - Method in class edu.cmu.tetrad.search.utils.Tetrad
Getter for the field j.
getJ() - Method in class edu.cmu.tetrad.search.work_in_progress.Sextad
Getter for the field j.
getJointMarginal(int[], int[]) - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
Computes the joint marginal probability for the specified variables and their corresponding values.
getJointMarginal(int[], int[]) - Method in interface edu.cmu.tetrad.bayes.BayesUpdater
Returns the joint marginal probability of the given variables taking the given values, given the evidence.
getJointMarginal(int[], int[]) - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
getJointMarginal.
getJointMarginal(int[], int[]) - Method in class edu.cmu.tetrad.bayes.Identifiability
getJointMarginal.
getJointMarginal(int[], int[]) - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Returns the joint marginal probability of the given variables taking the given values, given the evidence.
getJointMarginal(int[], int[]) - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
getJointMarginal.
getJointProbability(int[], int[]) - Method in class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
getJointProbability.
getJointProbabilityAll(int[]) - Method in class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
Get the joint probability of all nodes (variables).
getJPD() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
getJPD.
getK() - Method in class edu.cmu.tetrad.search.FastIca.IcaResult
Returns the pre-whitening matrix that projects data onto the first n.comp principal components.
getK() - Method in class edu.cmu.tetrad.search.utils.Sextad
Getter for the field k.
getK() - Method in class edu.cmu.tetrad.search.utils.Tetrad
Getter for the field k.
getK() - Method in class edu.cmu.tetrad.search.work_in_progress.Sextad
Getter for the field k.
getK() - Method in class edu.cmu.tetrad.util.PartialCorrelationPdf
Getter for the field k.
getKAddition() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Retrieves the value of the variable representing the k_addition.
getKAddition() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Retrieves the current value of the k_addition parameter.
getKDeletion() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Retrieves the value of the k_deletion field.
getKDeletion() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Retrieves the current value of the k_deletion parameter.
getknowledge() - Method in interface edu.cmu.tetrad.search.utils.R0R4Strategy
Returns the knowledge object used by the strategy.
getknowledge() - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyScoreBased
 
getknowledge() - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Retrieves the Knowledge object used by the FciOrientDataExaminationStrategy.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Fofc
Returns the knowledge associated with this object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Ftfc
Returns the knowledge associated with this algorithm.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Retrieves the knowledge associated with this object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Retrieves the knowledge associated with this object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskLofsConcatenated
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FasLofs
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Retrieves the knowledge of the current instance.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Boss
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossLingam
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cpc
Retrieves the knowledge associated with this object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fas
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMb
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMeasurement
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pc
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pcd
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMb
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.SingleGraphAlg
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Sp
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Retrieves the knowledge associated with the algorithm.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossDumb
Retrieves the knowledge object associated with this method.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPag
Retrieves the knowledge object associated with this method.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci
Returns the knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci
Retrieves the knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax
Retrieves the knowledge associated with the algorithm.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Retrieves the Knowledge object associated with this instance.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Retrieves the knowledge object associated with this method.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
Retrieves the knowledge object associated with this method.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci
Retrieves the knowledge associated with this method.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.RfciBsc
Retrieves the knowledge associated with this object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Retrieves the knowledge object associated with this algorithm.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarFci
Retrieves the knowledge object associated with this algorithm.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Returns the knowledge associated with this object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.Comparison
Retrieves the knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.algcomparison.statistic.KnowledgeSatisfied
 
getKnowledge() - Method in interface edu.cmu.tetrad.algcomparison.utils.HasKnowledge
Returns a knowledge object.
getKnowledge() - Method in class edu.cmu.tetrad.data.BoxDataSet
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
getKnowledge.
getKnowledge() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.data.DataModelList
Getter for the field knowledge.
getKnowledge() - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Retrieves the knowledge associated with the ICovarianceMatrix.
getKnowledge() - Method in class edu.cmu.tetrad.data.IndependenceFacts
Getter for the field knowledge.
getKnowledge() - Method in interface edu.cmu.tetrad.data.KnowledgeTransferable
getKnowledge.
getKnowledge() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.data.TimeSeriesData
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.Cpc
Returns the knowledge specification used in the search.
getKnowledge() - Method in class edu.cmu.tetrad.search.FaskOrig
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.Fci
Returns the background knowledge that was set.
getKnowledge() - Method in class edu.cmu.tetrad.search.FciMax
Retrieves the background knowledge that was set.
getKnowledge() - Method in class edu.cmu.tetrad.search.Fges
Returns the background knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.FgesMb
Returns the background knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.GFci
Returns the knowledge used in search.
getKnowledge() - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the knowledge object for the Markov checker.
getKnowledge() - Method in class edu.cmu.tetrad.search.Pc
Returns the knowledge specification used in the search.
getKnowledge() - Method in class edu.cmu.tetrad.search.Pcd
Retrieves the Knowledge object used by this method.
getKnowledge() - Method in class edu.cmu.tetrad.search.PcMb
Returns The knowledge used in search.
getKnowledge() - Method in class edu.cmu.tetrad.search.Rfci
Returns the knowledge used in search.
getKnowledge() - Method in class edu.cmu.tetrad.search.SpFci
Returns the knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.SvarFci
Returns the knowledge for the search.
getKnowledge() - Method in class edu.cmu.tetrad.search.SvarFges
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.utils.BesPermutation
Returns the knowledge that BES will use.
getKnowledge() - Method in class edu.cmu.tetrad.search.utils.DagToPag
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.utils.PcCommon
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.utils.PossibleMsepFci
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyScoreBased
Retrieves the knowledge associated with this instance.
getKnowledge() - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.utils.TsDagToPag
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.FasDci
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.FasLofs
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Returns the knowledge used in the IGFci algorithm.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Retrieves the Knowledge instance associated with this object.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.Mmhc
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.VcFas
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Getter for the field knowledge.
getKnowledge() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Getter for the field knowledge.
getKnowledge(Graph) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
getKnowledge.
getKnowledge(Graph) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
getKnowledge.
getKnowledge(Graph) - Static method in class edu.cmu.tetrad.study.performance.Comparison2
getKnowledge.
getKnowledgeGroups() - Method in class edu.cmu.tetrad.data.Knowledge
Getter for the field knowledgeGroups.
getKReorientation() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Retrieves the value of the k_reorient variable.
getKReorientation() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Retrieves the current value of the k_reorientation parameter.
getKsPValue(boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the Kolmorogov-Smirnov p-value for the given list of results.
getKsPValue(List<IndependenceResult>) - Method in class edu.cmu.tetrad.search.MarkovCheck
Calculates the Kolmogorov-Smirnov (KS) p-value for a list of independence test results.
getKsPValue(List<Double>) - Static method in class edu.cmu.tetrad.util.UniformityTest
Calculates the p-value of a list of points using the Kolmogorov-Smirnov test.
getKsPValue(List<Double>, double, double) - Static method in class edu.cmu.tetrad.util.UniformityTest
Calculates the p-value of a list of points using the Kolmogorov-Smirnov test.
getL() - Method in class edu.cmu.tetrad.search.utils.Sextad
Getter for the field l.
getL() - Method in class edu.cmu.tetrad.search.utils.Tetrad
Getter for the field l.
getL() - Method in class edu.cmu.tetrad.search.work_in_progress.Sextad
Getter for the field l.
getLag() - Method in class edu.cmu.tetrad.graph.TimeLagGraph.NodeId
Getter for the field lag.
getLag() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedParent
Returns the lag of the parent.
getLag() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedFactor
Returns the number of time steps back for this lagged factor.
getLag(String) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
getLag.
getLag(String) - Static method in class edu.cmu.tetrad.sem.LargeScaleSimulation
getLag.
getLag(String) - Static method in class edu.cmu.tetrad.study.performance.Comparison2
getLag.
getLag0Nodes() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Getter for the field lag0Nodes.
getLaggedFactor() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedEdge
Getter for the field laggedFactor.
getLaggedFactor(String) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.DisplayNameHandler
Parses the given string and returns the LaggedFactor it represents.
getLagGraph() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.GenePm
Gets the lag workbench that is wrapped.
getLags(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.RevealOutputGraph
Returns the lags of the parent variables for the given variable, provided parents have associated time lags; otherwise, returns null.
getLags(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.BiolinguaDigraph
Returns the lags of the parent variables for the given variable, provided parents have associated time lags; otherwise, returns null.
getLags(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealOutputGraph
Returns the lags of the parent variables for the given variable, provided parents have associated time lags; otherwise, returns null.
getLags(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealOutputGraph
Returns the lags of the parent variables for the given variable, provided parents have associated time lags; otherwise, returns null.
getLags(int) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.OutputGraph
Returns the lags of the parent variables for the given variable, provided parents have associated time lags; otherwise, returns null.
getLambda1() - Method in class edu.cmu.tetrad.search.Dagma
Retrieves the value of lambda1.
getLatentEffects(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch.LatentStructure
getLatentEffects.
getLatentNodes() - Method in class edu.cmu.tetrad.sem.SemPm
getLatentNodes.
getLatents() - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch.LatentStructure
getLatents.
getLatents(Graph) - Static method in class edu.cmu.tetrad.sem.ReidentifyVariables
getLatents.
getLatentsCov() - Method in class edu.cmu.tetrad.search.Mimbuild
Returns the inferred covariance matrix over the latent variables.
getLatentsCov() - Method in class edu.cmu.tetrad.search.MimbuildTrek
The covariance matrix over the latents that is implied by the clustering.
getLatestFilePath() - Method in class edu.cmu.tetrad.util.TetradLogger
Getter for the field latestFilePath.
getLengthWritten() - Method in interface edu.cmu.tetrad.util.TetradLogger.LogDisplayOutputStream
The total string length written to the text area.
getLhat() - Method in class edu.cmu.tetrad.sem.Ricf.RicfResult
Returns the "lhat" matrix.
getLik() - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianLikelihood.Ret
Returns the likelihood.
getLik() - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt.Ret
Returns the likelihood.
getLik(int, int[]) - Method in class edu.cmu.tetrad.search.score.MvpLikelihood
Returns the score of the node at index i, given its parents.
getLik(int, int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.MnlrLikelihood
Returns the likelihood of a child given its parents.
getLikelihood() - Method in class edu.cmu.tetrad.bayes.BayesProperties
Call after calling getLikelihoodP().
getLikelihood(int, int[]) - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianLikelihood
Returns the likelihood of variable i conditional on the given parents, assuming the continuous mixedVariables index by i or by the parents are jointly Gaussian conditional on the discrete comparison.
getLikelihoodRatioP() - Method in class edu.cmu.tetrad.bayes.EmBayesProperties
Calculates the p-value of the graph with respect to the given data.
getLikelihoodRatioP(Graph) - Method in class edu.cmu.tetrad.bayes.BayesProperties
Calculates the p-value of the graph with respect to the given data, against the complete model as an alternative.
getLineColor() - Method in class edu.cmu.tetrad.graph.Edge
Getter for the field lineColor.
getListOfExplicitlyForbiddenEdges() - Method in class edu.cmu.tetrad.data.Knowledge
getListOfExplicitlyForbiddenEdges.
getListOfExplicitlyRequiredEdges() - Method in class edu.cmu.tetrad.data.Knowledge
getListOfExplicitlyRequiredEdges.
getListOfForbiddenEdges() - Method in class edu.cmu.tetrad.data.Knowledge
getListOfForbiddenEdges.
getListOfRequiredEdges() - Method in class edu.cmu.tetrad.data.Knowledge
getListOfRequiredEdges.
getLocalPValues(IndependenceTest, List<IndependenceFact>) - Method in class edu.cmu.tetrad.search.MarkovCheck
Calculates the local p-values for a given independence test and a list of independence facts.
getLocalPValues(IndependenceTest, List<IndependenceFact>, Double) - Method in class edu.cmu.tetrad.search.MarkovCheck
Get Local P values with shuffle threshold provided.
getLocation(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Gets the location.
getLocation(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Gets the location.
getLocation(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Gets the location.
getLocation(String) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Gets the location.
getLocations() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
getLocations.
getLocations() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
getLocations.
getLocations() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Getter for the field locations.
getLocations() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Gets the locations.
getLoggerForClass(Class<?>) - Method in class edu.cmu.tetrad.util.TetradLogger
getLoggerForClass.
getLoggingDirectory() - Method in class edu.cmu.tetrad.util.TetradLogger
getLoggingDirectory.
getLoggingFilePrefix() - Method in class edu.cmu.tetrad.util.TetradLogger
getLoggingFilePrefix.
getLogLikelihood() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
The log likelihood of the regression
getLong(String) - Method in class edu.cmu.tetrad.util.Parameters
Returns the long value of the given parameter, looking up its default in the ParamDescriptions map.
getLong(String, long) - Method in class edu.cmu.tetrad.util.Parameters
Returns the long value of the given parameter, looking up its default in the ParamDescriptions map.
getLongDescription() - Method in class edu.cmu.tetrad.util.ParamDescription
Getter for the field longDescription.
getLow() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm.ParameterRange
Getter for the field low.
getLowerBoundDouble() - Method in class edu.cmu.tetrad.util.ParamDescription
Getter for the field lowerBoundDouble.
getLowerBoundInt() - Method in class edu.cmu.tetrad.util.ParamDescription
Getter for the field lowerBoundInt.
getLowerBoundLong() - Method in class edu.cmu.tetrad.util.ParamDescription
Getter for the field lowerBoundLong.
getLrScores() - Method in class edu.cmu.tetrad.search.FaskOrig
Returns a matrix of left-right scores for the search.
getM() - Method in class edu.cmu.tetrad.search.utils.Sextad
Getter for the field m.
getM() - Method in class edu.cmu.tetrad.search.work_in_progress.Sextad
Getter for the field m.
getMag() - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Returns the wrapped MAG.
getMag() - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Returns the wrapped MAG.
getMag() - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Returns the wrapped MAG.
getManipulatedBayesIm() - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
Getter for the field manipulatedBayesIm.
getManipulatedBayesIm() - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
Getter for the field manipulatedBayesIm.
getManipulatedBayesIm() - Method in class edu.cmu.tetrad.bayes.Identifiability
Getter for the field manipulatedBayesIm.
getManipulatedBayesIm() - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Returns the manipulated Bayes IM.
getManipulatedBayesIm() - Method in interface edu.cmu.tetrad.bayes.ManipulatingBayesUpdater
Returns the manipulated Bayes IM.
getManipulatedBayesIm() - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
Getter for the field manipulatedBayesIm.
getManipulatedGraph() - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
getManipulatedGraph.
getManipulatedGraph() - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
getManipulatedGraph.
getManipulatedGraph() - Method in class edu.cmu.tetrad.bayes.Identifiability
getManipulatedGraph.
getManipulatedGraph() - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Returns the manipulated graph.
getManipulatedGraph() - Method in interface edu.cmu.tetrad.bayes.ManipulatingBayesUpdater
Returns the manipulated graph.
getManipulatedGraph() - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
getManipulatedGraph.
getManipulatedGraph() - Method in class edu.cmu.tetrad.sem.SemUpdater
getManipulatedGraph.
getManipulatedSemIm() - Method in class edu.cmu.tetrad.sem.SemUpdater
getManipulatedSemIm.
getMarginal(int, int) - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
Returns the marginal probability of the given variable taking the given value, given the evidence.
getMarginal(int, int) - Method in interface edu.cmu.tetrad.bayes.BayesUpdater
Returns the marginal probability of the given variable taking the given value, given the evidence.
getMarginal(int, int) - Method in class edu.cmu.tetrad.bayes.CptInvariantMarginalCalculator
getMarginal.
getMarginal(int, int) - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
Returns the marginal probability of the given variable taking the given value, given the evidence.
getMarginal(int, int) - Method in class edu.cmu.tetrad.bayes.Identifiability
Returns the marginal probability of the given variable taking the given value, given the evidence.
getMarginal(int, int) - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Returns the marginal probability of the given variable taking the given value, given the evidence.
getMarginal(int, int) - Method in interface edu.cmu.tetrad.bayes.ManipulatingBayesUpdater
Returns the marginal probability of the given variable taking the given value, given the evidence.
getMarginal(int, int) - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
Returns the marginal probability of the given variable taking the given value, given the evidence.
getMarginalProbability(int) - Method in class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
getMarginalProbability.
getMarginalProbability(int, int) - Method in class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
getMarginalProbability.
getMarginals() - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Returns the marginals.
getMarkovBlanketSubgraphWithTargetNode(Graph, Node) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Calculates the subgraph over the Markov blanket of a target node for a DAG, CPDAG, MAG, or PAG.
getMarkovCheckRecord() - Method in class edu.cmu.tetrad.search.MarkovCheck
Generates the results for the given set of independence facts as a single record.
getMarkovCheckRecordString() - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the Markov check record as a string.
getMatrix() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
getMatrix.
getMatrix() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
getMatrix.
getMatrix() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Getter for the field matrix.
getMatrix() - Method in interface edu.cmu.tetrad.data.Covariances
Returns the underlying covariance matrix.
getMatrix() - Method in class edu.cmu.tetrad.data.CovariancesDoubleForkJoin
getMatrix.
getMatrix() - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Retrieves the covariance matrix.
getMatrix(int[]) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Getter for the field matrix.
getMax() - Method in class edu.cmu.tetrad.data.Histogram
For a continuous target, returns the maximum value of the values histogrammed, for the unconditioned data.
getMaxCoef() - Method in class edu.cmu.tetrad.search.CpdagParentDistancesFromTrue
Returns the maximum estimated coefficients for each edge.
getMaxDegree() - Method in class edu.cmu.tetrad.search.Fges
The maximum of parents any nodes can have in the output pattern.
getMaxDegree() - Method in class edu.cmu.tetrad.search.FgesMb
The maximum of parents any nodes can have in the output pattern.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.BasisFunctionBicScore
Retrieves the maximum degree from the underlying BIC score component.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.BdeScore
Gets the maximum degree of the BDe Score.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.BdeuScore
Returns the maximum degree of the BDeuScore object.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.DegenerateGaussianScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.EbicScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.GicScores
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.GraphScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.ImagesScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.IndTestScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.MvpScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.PoissonPriorScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in interface edu.cmu.tetrad.search.score.Score
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the maximum degree of the score.
getMaxDegree() - Method in class edu.cmu.tetrad.search.score.ZsbScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.SpFci
Returns The maximum indegree of the output graph.
getMaxDegree() - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Retrieves the maximum degree for the graph.
getMaxDegree() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Calculates the maximum degree based on the sample size.
getMaxDegree() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Retrieves the maximum degree value.
getMaxDegree() - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
The maximum of parents any nodes can have in an output pattern.
getMaxDegree() - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Retrieves the maximum allowable degree for nodes in the current scoring context.
getMaxDegree() - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.work_in_progress.MnlrScore
Returns the max degree, by default 1000.
getMaxDegree() - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Returns the max degree, by default 1000.
getMaxDiscriminatingPathLength() - Method in class edu.cmu.tetrad.search.Rfci
Returns the maximum length of any discriminating path, or -1 of unlimited.
getMaxDiscriminatingPathLength() - Method in class edu.cmu.tetrad.search.SpFci
Returns the maximum length of any discriminating path, or -1 of unlimited.
getMaxDiscriminatingPathLength() - Method in class edu.cmu.tetrad.search.SvarFci
Returns the maximum length of any discriminating path, or -1 of unlimited.
getMaxDiscriminatingPathLength() - Method in class edu.cmu.tetrad.search.utils.FciOrient
Returns the maximum path length, or -1 if unlimited.
getMaxDiscriminatingPathLength() - Method in class edu.cmu.tetrad.search.utils.TsDagToPag
Retrieves the maximum length of any discriminating path.
getMaximumCardinalityOrdering(Graph) - Static method in class edu.cmu.tetrad.bayes.GraphTools
Perform Tarjan and Yannakakis (1984) maximum cardinality search (MCS) to get the maximum cardinality ordering.
getMaxIndegree() - Method in class edu.cmu.tetrad.search.SvarFges
The maximum of parents any nodes can have in the output pattern.
getMaxIndex() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.Polynomial
Returns the highest variable index in any term.
getMaxIndex() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialTerm
Returns the highest variable index in this term.
getMaxit() - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Getter for the field maxit.
getMaxIterations() - Method in class edu.cmu.tetrad.cluster.KMeans
Return the maximum number of iterations, or -1 if the algorithm is allowed to run unconstrainted.
getMaxLag() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Getter for the field maxLag.
getMaxLag() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
getMaxLag.
getMaxLag() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
getMaxLag.
getMaxLag() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Maximum lag needed to fully represent the graph, which is the largest lag of any of the lagged factors stored in the graph.
getMaxLag() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
getMaxLag.
getMaxLag() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Maximum lag needed to fully represent the graph, which is the largest lag of any of the lagged factors stored in the graph.
getMaxLag() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Returns the max lag of the history.
getMaxLag() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialFunction
Returns the max lag of the history.
getMaxLag() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.UpdateFunction
getMaxLag.
getMaxLagAllowable() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
getMaxLagAllowable.
getMaxLagAllowable() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
getMaxLagAllowable.
getMaxLagAllowable() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Gets the maximum allowable lag.
getMaxLagAllowable() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Gets the maximum allowable lag.
getMaxMemUsage() - Method in class edu.cmu.tetrad.search.work_in_progress.Ion
getMaxMemUsage.
getMaxNumShifts() - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
Getter for the field maxNumShifts.
getMaxPathLength() - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Retrieves the maximum length of any path, or -1 if unlimited.
getMaxReachablePathLength() - Method in class edu.cmu.tetrad.search.Cfci
Returns the maximum length for any discriminating path.
getMaxShift() - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
Getter for the field maxShift.
getMaxTierForbiddenWithin() - Method in class edu.cmu.tetrad.data.Knowledge
getMaxTierForbiddenWithin.
getMaxTotalEffect(Node, Node) - Method in class edu.cmu.tetrad.search.IdaCheck
Returns the maximum total effect value between two nodes.
getMconn() - Method in class edu.cmu.tetrad.search.MarkovCheck.AllSubsetsIndependenceFacts
Returns the set of m-connection facts.
getMConnectedVars(Node, Set<Node>) - Method in class edu.cmu.tetrad.graph.Paths
Retrieves the set of nodes that are connected to the given node y and are also present in the set of nodes z.
getMConnectedVars(Node, Set<Node>, Map<Node, Set<Node>>) - Method in class edu.cmu.tetrad.graph.Paths
getMConnectedVars.
getMean(Node) - Method in interface edu.cmu.tetrad.sem.ISemIm
getMean.
getMean(Node) - Method in class edu.cmu.tetrad.sem.SemIm
Calculates the mean value associated with a given Node.
getMeanParameter(Node) - Method in class edu.cmu.tetrad.sem.SemPm
getMeanParameter.
getMeans() - Method in class edu.cmu.tetrad.search.work_in_progress.MixtureModel
getMeans.
getMeans() - Method in class edu.cmu.tetrad.sem.SemIm
getMeans.
getMeanStdDev(Node) - Method in interface edu.cmu.tetrad.sem.ISemIm
getMeanStdDev.
getMeanStdDev(Node) - Method in class edu.cmu.tetrad.sem.SemIm
Calculates the mean standard deviation for the given node.
getMeasuredData() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the measured data that is the result of a simulation, in the form of a three-dimensional double array.
getMeasuredData() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getMeasuredData.
getMeasuredNodes() - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the list of measured variables.
getMeasuredNodes() - Method in class edu.cmu.tetrad.bayes.BayesPm
Returns the measured nodes.
getMeasuredNodes() - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
getMeasuredNodes.
getMeasuredNodes() - Method in class edu.cmu.tetrad.bayes.MlBayesIm
getMeasuredNodes.
getMeasuredNodes() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
getMeasuredNodes.
getMeasuredNodes() - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
getMeasuredNodes.
getMeasuredNodes() - Method in class edu.cmu.tetrad.sem.DagScorer
getMeasuredNodes.
getMeasuredNodes() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Returns a list of measured nodes.
getMeasuredNodes() - Method in interface edu.cmu.tetrad.sem.ISemIm
getMeasuredNodes.
getMeasuredNodes() - Method in interface edu.cmu.tetrad.sem.Scorer
getMeasuredNodes.
getMeasuredNodes() - Method in class edu.cmu.tetrad.sem.SemIm
The list of measured nodes for the semPm.
getMeasuredNodes() - Method in class edu.cmu.tetrad.sem.SemPm
getMeasuredNodes.
getMeasuredNodes() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
The list of measured nodes for the semPm.
getMeasuredVarNames() - Method in class edu.cmu.tetrad.sem.SemPm
getMeasuredVarNames.
getMethod() - Method in class edu.cmu.tetrad.data.ContinuousDiscretizationSpec
Returns the value of the method used for discretization.
getMin() - Method in class edu.cmu.tetrad.data.Histogram
For a continuous target, returns the minimum value of the values histogrammed, for the unconditioned data.
getMinChunk(int) - Method in class edu.cmu.tetrad.search.SvarFges
Returns the minimum number of operations to perform before parallelizing.
getMinChunk(int) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Calculates the minimum chunk size for parallel processing.
getMinClusterSize() - Method in class edu.cmu.tetrad.search.Mimbuild
jf Clusters smaller than this size will be tossed out.
getMinClusterSize() - Method in class edu.cmu.tetrad.search.MimbuildTrek
Clusters smaller than this size will be tossed out.
getMinCoef() - Method in class edu.cmu.tetrad.search.CpdagParentDistancesFromTrue
Returns the minimum estimated coefficients for each edge.
getMinDepth() - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
getMinDepth.
getMinimum() - Method in class edu.cmu.tetrad.search.Mimbuild
Getter for the field minimum.
getMinTotalEffect(Node, Node) - Method in class edu.cmu.tetrad.search.IdaCheck
Gets the minimum total effect value between two nodes.
getMisclassificationTable(Graph, Graph) - Static method in class edu.cmu.tetrad.algcomparison.CompareTwoGraphs
Returns a misclassification comparison of two graphs.
getMissingValueMarker() - Method in class edu.cmu.tetrad.data.AbstractVariable
getMissingValueMarker.
getMissingValueMarker() - Method in class edu.cmu.tetrad.data.ContinuousVariable
getMissingValueMarker.
getMissingValueMarker() - Method in class edu.cmu.tetrad.data.DiscreteVariable
getMissingValueMarker.
getMissingValueMarker() - Method in interface edu.cmu.tetrad.data.Variable
Returns the name of the variable.
getMixedDataSet() - Method in class edu.cmu.tetrad.bayes.EmBayesEstimator
getMixedDataSet.
getMixedDataSet(DataModel) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
Returns the datamodel case to DataSet if it is mixed.
getMlag() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Getter for the field mlag.
getMlag() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraphParams
Returns the maximum lag.
getModelList() - Method in class edu.cmu.tetrad.data.DataModelList
Getter for the field modelList.
getModelPValue(List<List<Integer>>) - Method in class edu.cmu.tetrad.search.utils.ClusterSignificance
Returns the p-value for the given cluster.
getModelScore() - Method in class edu.cmu.tetrad.search.Fges
Returns the score of the final search model.
getModelScore() - Method in class edu.cmu.tetrad.search.FgesMb
Returns the score of the final search model.
getMsep() - Method in class edu.cmu.tetrad.search.MarkovCheck.AllSubsetsIndependenceFacts
Returns the set of m-separation facts.
getN() - Method in class edu.cmu.tetrad.data.Histogram
For a continuous target, returns the number of values histogrammed.
getN() - Method in class edu.cmu.tetrad.regression.RegressionResult
Getter for the field n.
getN() - Method in class edu.cmu.tetrad.search.utils.Sextad
Getter for the field n.
getN() - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Getter for the field n.
getN() - Method in class edu.cmu.tetrad.search.work_in_progress.Sextad
Getter for the field n.
getName() - Method in class edu.cmu.tetrad.calculator.expression.ConstantExpression
Getter for the field name.
getName() - Method in interface edu.cmu.tetrad.calculator.expression.ExpressionDescriptor
getName.
getName() - Method in class edu.cmu.tetrad.data.AbstractVariable
Getter for the field name.
getName() - Method in class edu.cmu.tetrad.data.BoxDataSet
Gets the name of the data set.
getName() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Gets the name of the covariance matrix.
getName() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Gets the name of the covariance matrix.
getName() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Gets the name of the covariance matrix.
getName() - Method in interface edu.cmu.tetrad.data.DataModel
getName.
getName() - Method in class edu.cmu.tetrad.data.DataModelList
Gets the name of the data model list.
getName() - Method in interface edu.cmu.tetrad.data.DataSet
getName.
getName() - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Gets the name of the covariance matrix.
getName() - Method in class edu.cmu.tetrad.data.IndependenceFacts
Getter for the field name.
getName() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Gets the name of the data set.
getName() - Method in class edu.cmu.tetrad.data.TimeSeriesData
Getter for the field name.
getName() - Method in class edu.cmu.tetrad.graph.GraphNode
Getter for the field name.
getName() - Method in interface edu.cmu.tetrad.graph.Node
Returns the name of this node.
getName() - Method in class edu.cmu.tetrad.graph.TimeLagGraph.NodeId
Getter for the field name.
getName() - Method in class edu.cmu.tetrad.sem.Parameter
Getter for the field name.
getName() - Method in class edu.cmu.tetrad.simulation.PRAOerrors
getName.
getName() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Getter for the field name.
getName() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbComponent
Returns the name.
getName() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Returns name of this matrix
getName() - Method in class edu.cmu.tetrad.util.dist.Beta
Please don't make me say it...
getName() - Method in class edu.cmu.tetrad.util.dist.ChiSquare
getName.
getName() - Method in class edu.cmu.tetrad.util.dist.Discrete
getName.
getName() - Method in interface edu.cmu.tetrad.util.dist.Distribution
Returns the name of the distribution.
getName() - Method in class edu.cmu.tetrad.util.dist.Exponential
getName.
getName() - Method in class edu.cmu.tetrad.util.dist.Gamma
getName.
getName() - Method in class edu.cmu.tetrad.util.dist.GaussianPower
Getter for the field name.
getName() - Method in class edu.cmu.tetrad.util.dist.Indicator
getName.
getName() - Method in class edu.cmu.tetrad.util.dist.LogNormal
getName.
getName() - Method in class edu.cmu.tetrad.util.dist.MixtureOfGaussians
getName.
getName() - Method in class edu.cmu.tetrad.util.dist.Normal
getName.
getName() - Method in class edu.cmu.tetrad.util.dist.Poisson
getName.
getName() - Method in class edu.cmu.tetrad.util.dist.SingleValue
Returns the name of the distribution.
getName() - Method in class edu.cmu.tetrad.util.dist.Split
getName.
getName() - Method in class edu.cmu.tetrad.util.dist.TruncatedNormal
getName.
getName() - Method in class edu.cmu.tetrad.util.dist.Uniform
getName.
getNameNoLag(Object) - Method in class edu.cmu.tetrad.search.SvarFci
Returns the name of the given object without any lagging characters.
getNameNoLag(Object) - Method in class edu.cmu.tetrad.search.SvarFges
Retrieves the name from the given object without any lag.
getNameNoLag(Object) - Method in class edu.cmu.tetrad.search.utils.SvarSetEndpointStrategy
getNameNoLag.
getNameNoLag(Object) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
getNameNoLag.
getNameNoLag(Object) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
getNameNoLag.
getNameNoLag(Object) - Static method in class edu.cmu.tetrad.study.performance.Comparison2
getNameNoLag.
getNames() - Method in class edu.cmu.tetrad.util.ParamDescriptions
getNames.
getNeighbors(Node) - Method in class edu.cmu.tetrad.search.FciOrientDijkstra.Graph
Returns the neighbors of a node, reachable via DijkstraEdges in the grph.
getNeighbors(Node) - Method in class edu.cmu.tetrad.search.utils.R5R9Dijkstra.Graph
Retrieves the filtered neighbors of a given node.
getNewSemIm() - Method in interface edu.cmu.tetrad.search.work_in_progress.Hbsms
getNewSemIm.
getNewSemIm() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
Getter for the field newSemIm.
getNewSemIm() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
Getter for the field newSemIm.
getNextOffset() - Method in class edu.cmu.tetrad.calculator.parser.ExpressionLexer
Getter for the field nextOffset.
getNextOffset() - Method in class edu.cmu.tetrad.calculator.parser.ExpressionParser
getNextOffset.
getNode() - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
Getter for the field node.
getNode(int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the name of the given node.
getNode(int) - Method in class edu.cmu.tetrad.bayes.BayesPm
Returns the node at the given index.
getNode(int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the name of the given node.
getNode(int) - Method in class edu.cmu.tetrad.bayes.Evidence
getNode.
getNode(int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Retrieves the node at the specified index.
getNode(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the name of the given node.
getNode(int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the name of the given node.
getNode(int) - Method in class edu.cmu.tetrad.sem.SemEvidence
getNode.
getNode(int) - Method in class edu.cmu.tetrad.sem.SemManipulation
getNode.
getNode(Node) - Method in class edu.cmu.tetrad.search.IndTestIod
Return the node associated with the given variable in the graph.
getNode(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
getNode.
getNode(String) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the name of the given node.
getNode(String) - Method in class edu.cmu.tetrad.bayes.BayesPm
Returns the node by the given name.
getNode(String) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
getNode.
getNode(String) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
getNode.
getNode(String) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
getNode.
getNode(String) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
getNode.
getNode(String) - Method in class edu.cmu.tetrad.graph.Dag
Retrieves the node in the graph with the specified name.
getNode(String) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getNode.
getNode(String) - Method in interface edu.cmu.tetrad.graph.Graph
getNode.
getNode(String) - Method in class edu.cmu.tetrad.graph.LagGraph
getNode.
getNode(String) - Method in class edu.cmu.tetrad.graph.SemGraph
getNode.
getNode(String) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves a Node from the graph based on the given name.
getNode(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Returns the Node with the given name.
getNode(String, int) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
getNode.
getNode1() - Method in class edu.cmu.tetrad.graph.Edge
Getter for the field node1.
getNode2() - Method in class edu.cmu.tetrad.graph.Edge
Getter for the field node2.
getNodeA() - Method in class edu.cmu.tetrad.sem.Parameter
Getter for the field nodeA.
getNodeB() - Method in class edu.cmu.tetrad.sem.Parameter
Getter for the field nodeB.
getNodeDists(Graph) - Static method in class edu.pitt.csb.mgm.MixedUtils
getNodeDists.
getNodeExpression(Node) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
getNodeExpression.
getNodeExpressionString(Node) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
getNodeExpressionString.
getNodeId(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
getNodeId.
getNodeIndex() - Method in class edu.cmu.tetrad.bayes.BayesPm
Returns the node index.
getNodeIndex() - Method in class edu.cmu.tetrad.sem.SemProposition
Returns the index of the node.
getNodeIndex(Node) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the index of the given node.
getNodeIndex(Node) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the index of the given node.
getNodeIndex(Node) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Returns the index of the given node in the nodes array.
getNodeIndex(Node) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the index of the given node.
getNodeIndex(Node) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the index of the given node.
getNodeIndex(Node) - Method in class edu.cmu.tetrad.sem.SemEvidence
getNodeIndex.
getNodeIndex(String) - Method in class edu.cmu.tetrad.bayes.Evidence
getNodeIndex.
getNodeIndex(String) - Method in class edu.cmu.tetrad.bayes.Proposition
getNodeIndex.
getNodeIndex(String) - Method in class edu.cmu.tetrad.sem.SemEvidence
getNodeIndex.
getNodeIndex(String) - Method in class edu.cmu.tetrad.sem.SemManipulation
getNodeIndex.
getNodeName(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.RevealOutputGraph
Returns the name of the variable at the given index.
getNodeName(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealOutputGraph
Returns the name of the variable at the given index.
getNodeName(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealOutputGraph
Returns the name of the variable at the given index.
getNodeName(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Returns the name of node i in this graph
getNodeName(int) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.OutputGraph
Returns the name of the variable at the given index.
getNodeNames() - Method in class edu.cmu.tetrad.graph.Dag
getNodeNames.
getNodeNames() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getNodeNames.
getNodeNames() - Method in interface edu.cmu.tetrad.graph.Graph
getNodeNames.
getNodeNames() - Method in class edu.cmu.tetrad.graph.LagGraph
getNodeNames.
getNodeNames() - Method in class edu.cmu.tetrad.graph.SemGraph
getNodeNames.
getNodeNames() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns a list of node names in the graph.
getNodes() - Method in class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
getNodes.
getNodes() - Method in class edu.cmu.tetrad.graph.Dag
getNodes.
getNodes() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getNodes.
getNodes() - Method in interface edu.cmu.tetrad.graph.Graph
getNodes.
getNodes() - Method in class edu.cmu.tetrad.graph.LagGraph
getNodes.
getNodes() - Method in class edu.cmu.tetrad.graph.SemGraph
getNodes.
getNodes() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves a list of nodes from the graph.
getNodes() - Method in class edu.cmu.tetrad.search.Fas
Retrieves the list of nodes in the graph.
getNodes() - Method in class edu.cmu.tetrad.search.Fasd
Retrieves the list of nodes from the current object.
getNodes() - Method in class edu.cmu.tetrad.search.FciOrientDijkstra.Graph
Returns the nodes in the graph.
getNodes() - Method in class edu.cmu.tetrad.search.Ida.NodeEffects
Returns the nodes.
getNodes() - Method in class edu.cmu.tetrad.search.IdaCheck
Returns a list of nodes.
getNodes() - Method in interface edu.cmu.tetrad.search.IFas
Returns the nodes searched over.
getNodes() - Method in class edu.cmu.tetrad.search.Pcd
Retrieves the list of nodes in the graph.
getNodes() - Method in class edu.cmu.tetrad.search.SvarFas
Retrieves the list of nodes from the current object.
getNodes() - Method in class edu.cmu.tetrad.search.utils.R5R9Dijkstra.Graph
Retrieves the nodes in the graph.
getNodes() - Method in class edu.cmu.tetrad.search.utils.Sextad
Returns the list of nodes.
getNodes() - Method in class edu.cmu.tetrad.search.utils.Tetrad
getNodes.
getNodes() - Method in class edu.cmu.tetrad.search.work_in_progress.FasFdr
Returns the nodes searched over.
getNodes() - Method in class edu.cmu.tetrad.search.work_in_progress.Sextad
getNodes.
getNodes() - Method in class edu.cmu.tetrad.search.work_in_progress.VcFas
getNodes.
getNodes() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves a list of nodes.
getNodesInEvidence() - Method in class edu.cmu.tetrad.sem.SemEvidence
getNodesInEvidence.
getNodesInTo(Node, Endpoint) - Method in class edu.cmu.tetrad.graph.Dag
Retrieves a list of nodes in the given graph that have edges pointing into the specified node and endpoint.
getNodesInTo(Node, Endpoint) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Nodes adjacent to the given node with the given proximal endpoint.
getNodesInTo(Node, Endpoint) - Method in interface edu.cmu.tetrad.graph.Graph
Nodes adjacent to the given node with the given proximal endpoint.
getNodesInTo(Node, Endpoint) - Method in class edu.cmu.tetrad.graph.LagGraph
Nodes adjacent to the given node with the given proximal endpoint.
getNodesInTo(Node, Endpoint) - Method in class edu.cmu.tetrad.graph.SemGraph
Nodes adjacent to the given node with the given proximal endpoint.
getNodesInTo(Node, Endpoint) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves a list of nodes that have an incoming edge from a specific node and endpoint.
getNodesOutTo(Node, Endpoint) - Method in class edu.cmu.tetrad.graph.Dag
Retrieves a list of nodes that have outgoing edges to a specified node and endpoint.
getNodesOutTo(Node, Endpoint) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Nodes adjacent to the given node with the given distal endpoint.
getNodesOutTo(Node, Endpoint) - Method in interface edu.cmu.tetrad.graph.Graph
Nodes adjacent to the given node with the given distal endpoint.
getNodesOutTo(Node, Endpoint) - Method in class edu.cmu.tetrad.graph.LagGraph
Nodes adjacent to the given node with the given distal endpoint.
getNodesOutTo(Node, Endpoint) - Method in class edu.cmu.tetrad.graph.SemGraph
Nodes adjacent to the given node with the given distal endpoint.
getNodesOutTo(Node, Endpoint) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves the list of nodes in a graph that have an outgoing edge to the given node and endpoint.
getNodeSubstitutedString(Node) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Retrieves the substituted string representation of a given Node.
getNodeSubstitutedString(Node, Map<String, Double>) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Retrieves the substituted string representation of a given Node.
getNodeType() - Method in class edu.cmu.tetrad.data.ContinuousVariable
Getter for the field nodeType.
getNodeType() - Method in class edu.cmu.tetrad.data.DiscreteVariable
Getter for the field nodeType.
getNodeType() - Method in class edu.cmu.tetrad.graph.GraphNode
Getter for the field nodeType.
getNodeType() - Method in interface edu.cmu.tetrad.graph.Node
Returns the node type for this node.
getNodeVariableType() - Method in class edu.cmu.tetrad.data.ContinuousVariable
Returns the node shape for this node.
getNodeVariableType() - Method in class edu.cmu.tetrad.data.DiscreteVariable
Returns the node shape for this node.
getNodeVariableType() - Method in class edu.cmu.tetrad.graph.GraphNode
Returns the node shape for this node.
getNodeVariableType() - Method in interface edu.cmu.tetrad.graph.Node
Returns the node shape for this node.
getNonadjacencies() - Method in class edu.cmu.tetrad.search.Pc
Returns the non-adjacencies of the searched graph.
getNoncolliders() - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Return noncolliders
getNoncolliderTriples() - Method in class edu.cmu.tetrad.search.utils.PcCommon
Getter for the field noncolliderTriples.
getNoncolliderTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Getter for the field noncolliderTriples.
getNoncolliderTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Getter for the field noncolliderTriples.
getNoncolliderTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Getter for the field noncolliderTriples.
getNoncolliderTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Getter for the field noncolliderTriples.
getNoncolliderTriples() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Getter for the field noncolliderTriples.
getNonparanormalTransformed(DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
getNonparanormalTransformed.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFn
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFp
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFpr
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyPrecision
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyRecall
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTn
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTp
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTpr
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorF1
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorPrecision
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorRecall
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestralPrecision
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestralRecall
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFn
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFp
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFpr
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecision
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecisionCommonEdges
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecall
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecallCommonEdges
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTn
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTp
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeTrue
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicDiff
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicDiffPerRecord
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicTrue
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedFP
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedLatentPrecision
Calculates the normalized value of a given statistic value.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedPrecision
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedRecall
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedTP
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedTrue
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalseNegativeBidirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalsePositiveBidirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorTruePositiveBidirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonMeasuredAncestorRecallBidirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.CorrectSkeleton
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathPrecision
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathRecall
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.DensityEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.DensityTrue
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ElapsedCpuTime
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.F1Adj
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.F1All
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.F1Arrow
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.FalseNegativesAdjacencies
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.FalsePositiveAdjacencies
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.FBetaAdj
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderAlternative
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderNull
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.GraphExactlyRight
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaAverageSquaredDistance
Returns a normalized value of the statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMaxSquaredDiffEstTrue
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMinSquaredDiffEstTrue
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgSquaredDifference
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaMaximumSquaredDifference
Returns a normalized value of the statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaMinimumSquaredDifference
Returns a normalized value of the statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst2
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedOrientationRatioEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliesLegalMag
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.KnowledgeSatisfied
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalseNegativeBidirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalsePositiveBidirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorRecallBidirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorTruePositiveBidirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.LegalPag
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.LocalGraphPrecision
This method returns the normalized value of a given statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.LocalGraphRecall
 
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MagCgScore
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MagDgScore
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MagSemScore
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPasses
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPassesBestOf10
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingP
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingPBestOf10
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialP
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialPBestOf10
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffP
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffPBestOf10
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPasses
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPassesBestOf10
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrAdj
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrArrow
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.Maximal
Returns the normalized value of the given statistic value.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.MaximalityCondition
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NoAlmostCyclicPathsCondition
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NoCyclicPathsCondition
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesPrecision
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesRecall
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NonancestorPrecision
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NonancestorRecall
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedF1
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedPrecision
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedRecall
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumAmbiguousTriples
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsNotInUnshieldedCollidersEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberCollidersEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInCollidersEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInUnshieldedCollidersEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesTrue
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesTrue
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberTailsEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberUnshieldedCollidersEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedBothNonancestorAncestor
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesTrue
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredDD
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredNL
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredPD
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredPL
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCommonMeasuredAncestorBidirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDefiniteDirectedEdgeAncestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeConfounded
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeNonAncestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleEdges
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeAncestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeNonAncestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleVisibleNonancestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectBidirected
Returns the normalized value of the given statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectDDAncestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectPDAncestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectVisibleEdges
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCoveringAdjacenciesInPag
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyDirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyNotDirectedPaths
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeAncestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeBnaMeasuredCounfounded
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNoMeasureAncestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNotAncNotRev
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeReversed
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdges
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsTrue
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedShouldBePartiallyDirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumEdgeInEstInTrue
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumGenuineAdjacenciesInPag
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectDDAncestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectPDAncestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectVisibleAncestors
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumLatentCommonAncestorBidirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumNondirectedEdges
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumParametersEst
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumPartiallyOrientedEdges
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumPossiblyDirected
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumUndirectedEdges
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdgeEst
Returns the normalized value of the given value.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdges
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdgeTrue
Returns the normalized value of a given statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.OrientationPrecision
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.OrientationRecall
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyPrecision
Retrieves the normalized value of a given statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyRecall
Retrieves the normalized value of this statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ParameterColumn
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.PercentAmbiguous
Calculates the normalized value of a statistic given the original value.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.PercentBidirectedEdges
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedEst
Retrieves the normalized value of the given statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedTrue
Calculates the normalized value of a given statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.PvalueDistanceToAlpha
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.PvalueUniformityUnderNull
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPathF1
Retrieves the normalized value of the statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPrecision
Returns the normalized value of the statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedRecall
Retrieves the normalized value of the statistic.
getNormValue(double) - Method in interface edu.cmu.tetrad.algcomparison.statistic.Statistic
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.StructuralHammingDistance
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TailPrecision
Retrieves the normalized value of the statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TailRecall
Returns the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesArrows
Retrieves the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesTails
Retrieves the normalized value of the given statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveArrow
Retrieves the normalized value of the statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveTails
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionArrow
Retrieves the normalized value of the statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionTails
Calculates the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallArrows
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallTails
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveArrow
Retrieves the normalized value of the statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveDirectedPathNonancestor
Retrieves the normalized value of a statistic.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveTails
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalseNegative
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalsePositive
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCyclePrecision
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleRecall
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNormValue(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleTruePositive
Returns a mapping of the statistic to the interval [0, 1], with higher being better.
getNparents() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Sets the number of parents.
getNumAllowed(int) - Method in class edu.cmu.tetrad.bayes.Proposition
getNumAllowed.
getNumAllowedCategories(int) - Method in class edu.cmu.tetrad.bayes.Proposition
getNumAllowedCategories.
getNumber() - Method in class edu.cmu.tetrad.sem.ParamConstraint
Getter for the field number.
getNumberFormat() - Method in class edu.cmu.tetrad.data.BoxDataSet
getNumberFormat.
getNumberFormat() - Method in interface edu.cmu.tetrad.data.DataSet
The number format of the dataset.
getNumberFormat() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getNumberFormat.
getNumberFormat() - Method in class edu.cmu.tetrad.util.NumberFormatUtil
getNumberFormat.
getNumberOfArguments() - Method in interface edu.cmu.tetrad.calculator.expression.ExpressionSignature
getNumberOfArguments.
getNumberOfColumns(DataModel) - Static method in class edu.cmu.tetrad.util.MultidataUtils
getNumberOfColumns.
getNumberOfNodes() - Method in class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
getNumberOfNodes.
getNumCases() - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Returns the number of cases for the data.
getNumCategories() - Method in class edu.cmu.tetrad.data.DiscreteVariable
getNumCategories.
getNumCategories(int) - Method in class edu.cmu.tetrad.bayes.Evidence
getNumCategories.
getNumCategories(int) - Method in class edu.cmu.tetrad.bayes.Proposition
getNumCategories.
getNumCategories(Node) - Method in class edu.cmu.tetrad.bayes.BayesPm
Returns the number of values for the given node.
getNumCauses() - Method in class edu.cmu.tetrad.search.Cstar.Record
Retrieves the number of possible causes of the target in a record.
getNumCells() - Method in class edu.cmu.tetrad.search.utils.AdTree
Return the number of cells in the table.
getNumCells() - Method in class edu.cmu.tetrad.util.MultiDimIntTable
Returns the number of cells in the table.
getNumCellsPerDish() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the number of cells per dish.
getNumCellsPerDish() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getNumCellsPerDish.
getNumClusters() - Method in class edu.cmu.tetrad.cluster.KMeans
getNumClusters.
getNumClusters() - Method in class edu.cmu.tetrad.data.Clusters
Getter for the field numClusters.
getNumColumns() - Method in interface edu.cmu.tetrad.bayes.CptMap
Retrieves the number of columns in the CptMap.
getNumColumns() - Method in class edu.cmu.tetrad.bayes.CptMapCounts
Returns the number of columns in the probability map.
getNumColumns() - Method in class edu.cmu.tetrad.bayes.CptMapProbs
Returns the number of columns in the probability map.
getNumColumns() - Method in class edu.cmu.tetrad.data.BoxDataSet
getNumColumns.
getNumColumns() - Method in interface edu.cmu.tetrad.data.DataSet
getNumColumns.
getNumColumns() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getNumColumns.
getNumColumns() - Method in class edu.cmu.tetrad.util.Matrix
getNumColumns.
getNumColumns() - Method in class edu.cmu.tetrad.util.TextTable
getNumColumns.
getNumColumns(int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the number of columns.
getNumColumns(int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the number of columns.
getNumColumns(int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Returns the number of columns in the specified node.
getNumColumns(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the number of columns.
getNumColumns(int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the number of columns.
getNumCombinations(int, int) - Static method in class edu.cmu.tetrad.util.ChoiceGenerator
Returns the number of combinations of a choose b.
getNumCombinations(int, int) - Static method in class edu.cmu.tetrad.util.SublistGenerator
getNumCombinations.
getNumCoveringAdjacenciesInPag(Graph, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns the number of covering edges in the given estimated partial ancestral graph (PAG) with respect to the given true PAG.
getnumCPDAGsToStore() - Method in class edu.cmu.tetrad.search.SvarFges
Getter for the field numCPDAGsToStore.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.algorithm.ExternalAlgorithm
getNumDataModels.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.NLSemSimulation
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
Returns the number of data models.
getNumDataModels() - Method in interface edu.cmu.tetrad.algcomparison.simulation.Simulation
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.SingleDatasetSimulation
Returns the number of data models (1).
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs
Returns the number of data models.
getNumDataModels() - Method in class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
Returns the number of data models.
getNumDimensions() - Method in class edu.cmu.tetrad.util.MultiDimIntTable
Returns the number of dimensions in the table.
getNumDishes() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the number of dishes to simulate.
getNumDishes() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getNumDishes.
getNumEdges() - Method in class edu.cmu.tetrad.graph.Dag
getNumEdges.
getNumEdges() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getNumEdges.
getNumEdges() - Method in interface edu.cmu.tetrad.graph.Graph
getNumEdges.
getNumEdges() - Method in class edu.cmu.tetrad.graph.LagGraph
getNumEdges.
getNumEdges() - Method in class edu.cmu.tetrad.graph.SemGraph
getNumEdges.
getNumEdges() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves the number of edges in the graph.
getNumEdges() - Method in class edu.cmu.tetrad.search.Grasp
Returns the number of edges in the DAG implied by the discovered permutation.
getNumEdges() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
getNumEdges.
getNumEdges() - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
getNumEdges.
getNumEdges() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Returns the Total # of edges in this graph
getNumEdges() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field numEdges.
getNumEdges(Node) - Method in class edu.cmu.tetrad.graph.Dag
Returns the number of edges connected to the specified node.
getNumEdges(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getNumEdges.
getNumEdges(Node) - Method in interface edu.cmu.tetrad.graph.Graph
getNumEdges.
getNumEdges(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getNumEdges.
getNumEdges(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getNumEdges.
getNumEdges(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves the number of edges connected to a specific node.
getNumEffects() - Method in class edu.cmu.tetrad.search.Cstar.Record
Retrieves the number of possible effects of the target in a record.
getNumericalMean() - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Returns the numerical mean of the empirical cumulative distribution function (CDF).
getNumericalVariance() - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Returns the numerical variance of the empirical cumulative distribution function (CDF).
getNumFactors() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
getNumFactors.
getNumFactors() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
getNumFactors.
getNumFactors() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Returns the number of factors represented in the graph.
getNumFactors() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
getNumFactors.
getNumFactors() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity
Returns the number of factors.
getNumFactors() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph
Returns the number of factors.
getNumFactors() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Returns the number of factors represented in the graph.
getNumFactors() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Returns the number of factors in the history.
getNumFactors() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialFunction
Returns the number of factors in the history.
getNumFactors() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.UpdateFunction
getNumFactors.
getNumFixedParams() - Method in class edu.cmu.tetrad.sem.SemIm
getNumFixedParams.
getNumFreeParams() - Method in class edu.cmu.tetrad.sem.DagScorer
getNumFreeParams.
getNumFreeParams() - Method in interface edu.cmu.tetrad.sem.ISemIm
getNumFreeParams.
getNumFreeParams() - Method in interface edu.cmu.tetrad.sem.Scorer
getNumFreeParams.
getNumFreeParams() - Method in class edu.cmu.tetrad.sem.SemIm
getNumFreeParams.
getNumFunctions() - Method in class edu.cmu.tetrad.search.test.ConditionalCorrelationIndependence
Retrieves the number of functions used in the ConditionalCorrelationIndependence analysis.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.Fasd
Returns the number of conditional independence tests done in the course of search.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.GrowShrink
getNumIndependenceTests.
getNumIndependenceTests() - Method in interface edu.cmu.tetrad.search.IMbSearch
Number of independent tests.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.Pcd
Retrieves the number of independence tests performed by the graph search.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.PcMb
Returns the number of independence tests performed during the most recent search.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.SvarFas
Returns the number of independence tests.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.work_in_progress.FasDci
Getter for the field numIndependenceTests.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.work_in_progress.FasFdr
Returns the nubmer of independence tests done in the course of the search.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.work_in_progress.Iamb
getNumIndependenceTests.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.work_in_progress.IambnPc
getNumIndependenceTests.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.work_in_progress.InterIamb
getNumIndependenceTests.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.work_in_progress.Mmmb
getNumIndependenceTests.
getNumIndependenceTests() - Method in class edu.cmu.tetrad.search.work_in_progress.VcFas
Getter for the field numIndependenceTests.
getNumInducedAdjacenciesInPag(Graph, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Calculates the number of induced adjacencies in the given estiamted Partial Ancestral (PAG) with respect to the given true PAG.
getNumInitialLags() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Getter for the field numInitialLags.
getNumIterations() - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbsParams
Getter for the field numIterations.
getNumNodes() - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the name of the given node.
getNumNodes() - Method in class edu.cmu.tetrad.bayes.BayesPm
Returns the number of nodes.
getNumNodes() - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
getNumNodes.
getNumNodes() - Method in class edu.cmu.tetrad.bayes.Evidence
getNumNodes.
getNumNodes() - Method in class edu.cmu.tetrad.bayes.MlBayesIm
getNumNodes.
getNumNodes() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
getNumNodes.
getNumNodes() - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
getNumNodes.
getNumNodes() - Method in class edu.cmu.tetrad.graph.Dag
getNumNodes.
getNumNodes() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getNumNodes.
getNumNodes() - Method in interface edu.cmu.tetrad.graph.Graph
getNumNodes.
getNumNodes() - Method in class edu.cmu.tetrad.graph.LagGraph
getNumNodes.
getNumNodes() - Method in class edu.cmu.tetrad.graph.SemGraph
getNumNodes.
getNumNodes() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Gets the number of nodes in the graph.
getNumNodes() - Method in class edu.cmu.tetrad.sem.SemEvidence
getNumNodes.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.Beta
Uh, there are 2 parameters...
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.ChiSquare
getNumParameters.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.Discrete
getNumParameters.
getNumParameters() - Method in interface edu.cmu.tetrad.util.dist.Distribution
Returns the number of parameters in the distribution.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.Exponential
getNumParameters.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.Gamma
getNumParameters.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.GaussianPower
getNumParameters.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.Indicator
getNumParameters.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.LogNormal
getNumParameters.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.MixtureOfGaussians
getNumParameters.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.Normal
getNumParameters.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.Poisson
getNumParameters.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.SingleValue
Returns the number of parameters in the distribution.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.Split
getNumParameters.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.TruncatedNormal
getNumParameters.
getNumParameters() - Method in class edu.cmu.tetrad.util.dist.Uniform
getNumParameters.
getNumParents(int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the number of parents for the given node.
getNumParents(int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the number of parents for the given node.
getNumParents(int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Returns the number of parents for the given node.
getNumParents(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the number of parents for the given node.
getNumParents(int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the number of parents for the given node.
getNumParents(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Digraph
Returns the number of parents of node i.
getNumParents(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity
Returns the number of parents of the given factor.
getNumParents(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph
Returns the number of parents of the given factor.
getNumRandomCalls() - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field numRandomCalls.
getNumRegressors() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
The number of regressors.
getNumRegressors() - Method in class edu.cmu.tetrad.regression.RegressionResult
getNumRegressors.
getNumRestarts() - Method in interface edu.cmu.tetrad.sem.SemOptimizer
getNumRestarts.
getNumRestarts() - Method in class edu.cmu.tetrad.sem.SemOptimizerEm
Returns the number of restarts for the optimization process.
getNumRestarts() - Method in class edu.cmu.tetrad.sem.SemOptimizerPowell
getNumRestarts.
getNumRestarts() - Method in class edu.cmu.tetrad.sem.SemOptimizerRegression
getNumRestarts.
getNumRestarts() - Method in class edu.cmu.tetrad.sem.SemOptimizerRicf
getNumRestarts.
getNumRestarts() - Method in class edu.cmu.tetrad.sem.SemOptimizerScattershot
getNumRestarts.
getNumRows() - Method in interface edu.cmu.tetrad.bayes.CptMap
Retrieves the number of rows in the CptMap.
getNumRows() - Method in class edu.cmu.tetrad.bayes.CptMapCounts
Returns the number of rows in the probability map.
getNumRows() - Method in class edu.cmu.tetrad.bayes.CptMapProbs
Returns the number of rows in the probability map.
getNumRows() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
getNumRows.
getNumRows() - Method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
getNumRows.
getNumRows() - Method in class edu.cmu.tetrad.data.BoxDataSet
getNumRows.
getNumRows() - Method in interface edu.cmu.tetrad.data.DataSet
getNumRows.
getNumRows() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getNumRows.
getNumRows() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
getNumRows.
getNumRows() - Method in class edu.cmu.tetrad.util.Matrix
getNumRows.
getNumRows() - Method in class edu.cmu.tetrad.util.TextTable
getNumRows.
getNumRows(int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the number of rows.
getNumRows(int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the number of rows.
getNumRows(int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Retrieves the number of rows in the specified node.
getNumRows(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the number of rows.
getNumRows(int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the number of rows.
getNumSamplesPerDish() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the number of samples generated per dish in the measurement model.
getNumSamplesPerDish() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getNumSamplesPerDish.
getNumTerms() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.Polynomial
Returns the number of terms.
getNumTests(boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the number of tests for the given list of results.
getNumTiers() - Method in class edu.cmu.tetrad.data.Knowledge
getNumTiers.
getNumTimePoints() - Method in class edu.cmu.tetrad.data.TimeSeriesData
getNumTimePoints.
getNumValues(String) - Method in class edu.cmu.tetrad.util.Parameters
Returns the number of values for the parameter.
getNumVariables() - Method in class edu.cmu.tetrad.bayes.Proposition
getNumVariables.
getNumVariables() - Method in class edu.cmu.tetrad.sem.SemProposition
Returns the number of variables in the current object.
getNumVariables() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialTerm
Returns the number of variables in this term.
getNumVars() - Method in class edu.cmu.tetrad.data.TimeSeriesData
getNumVars.
getNumVars() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field numVars.
getNy0() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
The number of data points with target = 0.
getNy1() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
The number of data points with target = 1.
getObject(int, int) - Method in class edu.cmu.tetrad.data.BoxDataSet
getObject.
getObject(int, int) - Method in interface edu.cmu.tetrad.data.DataSet
getObject.
getObject(int, int) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getObject.
getObservedCounts(Node, BayesPm, BayesIm) - Method in class edu.cmu.tetrad.bayes.BdeMetricCache
This method is used in testing and debugging and not in the BDe metric calculations.
getOhat() - Method in class edu.cmu.tetrad.sem.Ricf.RicfResult
Returns the ohat matrix.
getOneMbDag(Graph) - Static method in class edu.cmu.tetrad.search.utils.MbUtils
Returns an example DAG from the given MB CPDAG.
getOrder() - Method in class edu.cmu.tetrad.search.PermutationSearch
Retrieves the order list.
getOrder() - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Returns the order.
getOrder() - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Returns the order.
getOrder() - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Returns the order.
getOrderedPairs() - Method in class edu.cmu.tetrad.search.IdaCheck
Retrieves a list of OrderedPair objects representing all possible pairs of distinct nodes in the graph.
getOrderShallow() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns the current permutation without making a copy.
getOrientPrecision() - Method in class edu.cmu.tetrad.simulation.PRAOerrors
getOrientPrecision.
getOrientRecall() - Method in class edu.cmu.tetrad.simulation.PRAOerrors
getOrientRecall.
getOrients() - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Return orients
getOriginalSemIm() - Method in interface edu.cmu.tetrad.search.work_in_progress.Hbsms
getOriginalSemIm.
getOriginalSemIm() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
Getter for the field originalSemIm.
getOriginalSemIm() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
Getter for the field originalSemIm.
getOut() - Method in class edu.cmu.tetrad.search.Fges
Returns the output stream used for printing.
getOut() - Method in class edu.cmu.tetrad.search.FgesMb
Returns the output stream associated with this object.
getOut() - Method in class edu.cmu.tetrad.search.SvarFges
Getter for the field out.
getOut() - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Getter for the field out.
getOut() - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Retrieves the current PrintStream used for output by the IGFci algorithm.
getOut() - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Retrieves the current PrintStream used for standard output.
getOut() - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Getter for the field out.
getOut() - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Getter for the field out.
getOutdegree(Node) - Method in class edu.cmu.tetrad.graph.Dag
Returns the outdegree of the given node.
getOutdegree(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getOutdegree.
getOutdegree(Node) - Method in interface edu.cmu.tetrad.graph.Graph
getOutdegree.
getOutdegree(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getOutdegree.
getOutdegree(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getOutdegree.
getOutdegree(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves the outdegree of the specified node in the graph.
getOutputs() - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Getter for the field outputs.
getOutputs(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch.LatentStructure
getOutputs.
getP() - Method in class edu.cmu.tetrad.data.AndersonDarlingTest
Constructs an Anderson-Darling test for the given column of data.
getP() - Method in class edu.cmu.tetrad.data.GeneralAndersonDarlingTest
Getter for the field p.
getP() - Method in class edu.cmu.tetrad.data.MultiGeneralAndersonDarlingTest
Getter for the field p.
getP() - Method in class edu.cmu.tetrad.regression.RegressionResult
Getter for the field p.
getPag() - Method in class edu.cmu.tetrad.search.utils.PossibleMConnectingPath
Getter for the field pag.
getPag(Graph) - Method in class edu.cmu.tetrad.util.PagCache
Returns the PAG (Partial Ancestral Graph) corresponding to the given DAG (Directed Acyclic Graph).
getPag(Graph, Knowledge, boolean) - Method in class edu.cmu.tetrad.util.PagCache
Returns the PAG (Partial Ancestral Graph) corresponding to the given DAG (Directed Acyclic Graph).
getParam2() - Method in class edu.cmu.tetrad.sem.ParamConstraint
Getter for the field param2.
getParamComparison(Parameter, Parameter) - Method in class edu.cmu.tetrad.sem.SemPm
getParamComparison.
getParameter() - Method in class edu.cmu.tetrad.sem.Mapping
Getter for the field parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.Beta
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.ChiSquare
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.Discrete
Returns the index'th parameter.
getParameter(int) - Method in interface edu.cmu.tetrad.util.dist.Distribution
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.Exponential
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.Gamma
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.GaussianPower
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.Indicator
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.LogNormal
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.MixtureOfGaussians
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.Normal
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.Poisson
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.SingleValue
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.Split
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.TruncatedNormal
Returns the index'th parameter.
getParameter(int) - Method in class edu.cmu.tetrad.util.dist.Uniform
Returns the index'th parameter.
getParameter(Node, Node) - Method in class edu.cmu.tetrad.sem.SemPm
getParameter.
getParameter(String) - Method in class edu.cmu.tetrad.sem.SemPm
getParameter.
getParameterEstimationInitializationExpression(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the initialization expression for a given parameter used in parameter estimation.
getParameterEstimationInitializationExpressionString(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Returns the initialization expression string for the given parameter.
getParameterExpression(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the expression associated with the given parameter.
getParameterExpressionString(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Returns the expression string associated with the given parameter.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.Beta
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.ChiSquare
Returns the name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.Discrete
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in interface edu.cmu.tetrad.util.dist.Distribution
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.Exponential
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.Gamma
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.GaussianPower
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.Indicator
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.LogNormal
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.MixtureOfGaussians
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.Normal
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.Poisson
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.SingleValue
Returns the name of the index'th parameter.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.Split
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.TruncatedNormal
The name of the index'th parameter, for display purposes.
getParameterName(int) - Method in class edu.cmu.tetrad.util.dist.Uniform
The name of the index'th parameter, for display purposes.
getParameterNames() - Static method in class edu.cmu.tetrad.bayes.BayesPm
Returns the parameter names.
getParameterNames() - Static method in class edu.cmu.tetrad.bayes.MlBayesIm
getParameterNames.
getParameterNames() - Static method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the names of the parameters required for a certain operation.
getParameterNames() - Static method in class edu.cmu.tetrad.sem.SemIm
getParameterNames.
getParameterRange(Edge) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
getParameterRange.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Bpc
Retrieves the list of parameters used by the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Fofc
Returns a list of parameters for the search algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Ftfc
Retrieves the list of parameters supported by this algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Dagma
Retrieves the list of parameters used by the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.DirectLingam
Returns a list of parameters for the DirectLingam algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Returns the list of parameter names that are used by the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Returns the list of parameter names that are used by the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingam
Returns a list of parameters used by the getParameters method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingD
Retrieves the list of parameters used by this method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.ExternalAlgorithm
getParameters.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.FirstInflection
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.mixed.Mgm
Returns the list of parameters required by the getParameters method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskLofsConcatenated
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FasLofs
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Retrieves the list of parameters required for the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Boss
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossLingam
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cpc
Retrieves the list of parameters used in this method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fas
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMb
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMeasurement
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pc
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pcd
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMb
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.RestrictedBoss
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.SingleGraphAlg
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Sp
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Retrieves the list of parameters used for the BFCI (Best-order FCI) algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossDumb
Retrieves the list of parameters used by the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPag
Retrieves the list of parameters used by the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Ccd
Retrieves the parameters for the search algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci
Returns the list of parameters used by the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci
Retrieves the list of parameters used by this algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax
Returns the list of parameters used by the method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Returns a list of parameters used to configure the search algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Retrieves the list of parameters used by the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
Retrieves the list of parameters used by the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci
Retrieves the list of parameters for the method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.RfciBsc
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Returns the list of parameters used by the method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarFci
Retrieves the list of parameters required for this method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Returns the list of parameters required by this method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.other.FactorAnalysis
Retrieves the parameters for the current instance of the FactorAnalysis class.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.other.Glasso
Retrieves a list of parameters used by the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Eb
Returns the list of parameters that are used by the class.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.FaskPw
Retrieves the list of parameters required for the algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R1
Retrieves the list of parameters for the current instance.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R2
Retrieves the list of parameters for the current instance of the class.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R3
Retrieves the list of parameters for the method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Rskew
Retrieves a list of parameters required for the current instance of the class.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.RskewE
Retrieves the list of parameters required for the current instance of the class.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Skew
Retrieves the list of parameter names that are used by this method and its associated algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.SkewE
Returns the list of parameters for the current instance of the class.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Tanh
Returns the parameters required by the current algorithm.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.algorithm.StARS
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.graph.Cyclic
Returns the parameters that this graph uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.graph.ErdosRenyi
Returns the parameters that this graph uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.graph.RandomForward
Returns the parameters that this graph uses.
getParameters() - Method in interface edu.cmu.tetrad.algcomparison.graph.RandomGraph
Returns the parameters that this graph uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.graph.RandomSingleFactorMim
Returns the parameters that this graph uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.graph.RandomTwoFactorMim
Returns the parameters that this graph uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.graph.ScaleFree
Returns the parameters that this graph uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.graph.SingleGraph
Returns the parameters that this graph uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.BasisFunctionBicTest
Retrieves the parameters required for the Basis Function BIC test.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.BdeuTest
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.CciTest
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.ChiSquare
Retrieves the parameters required by the Chi Square Test.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.ConditionalGaussianLRT
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.DegenerateGaussianLRT
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.DiscreteBicTest
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.FisherZ
Retrieves the parameters of the Fisher Z test.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.GICScoreTests
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.GSquare
Returns the parameters that this search uses.
getParameters() - Method in interface edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.Kci
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.MagSemBicTest
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.Mnlrlrt
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.MSeparationTest
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.MultinomialLogisticRegressionWald
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.Mvplrt
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.PoissonPriorTest
Retrieves the parameters required for the Poisson Prior test.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.PositiveCorr
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.ProbabilisticTest
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.SemBicDTest
Returns the list of parameters used in this method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.independence.SemBicTest
Retrieves the parameters required for the SEM BIC test.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.BasisFunctionBicScore
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.BdeuScore
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.ConditionalGaussianBicScore
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.DegenerateGaussianBicScore
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.DiscreteBicScore
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.EbicScore
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.FisherZScore
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.GicScores
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.MagDgBicScore
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.MSeparationScore
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.MVPBicScore
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.PoissonPriorScore
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.PositiveCorrScore
Returns the parameters that this search uses.
getParameters() - Method in interface edu.cmu.tetrad.algcomparison.score.ScoreWrapper
Returns the parameters that this search uses.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.SemBicScore
Returns a list of parameters applicable to this method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.SemBicScoreDeterministic
Retrieves the list of parameters required for the getScore() method.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.score.ZhangShenBoundScore
Returns the list of parameters required for the Zhang-Shen Bound Score.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Retrieves the parameters required for the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.NLSemSimulation
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Retrieves the parameters required for the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
Returns the list of parameters used in the simulation.
getParameters() - Method in interface edu.cmu.tetrad.algcomparison.simulation.Simulation
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.SingleDatasetSimulation
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
Returns the list of parameters used in the simulation.
getParameters() - Method in interface edu.cmu.tetrad.algcomparison.utils.HasParameters
Returns the list of parameter names that are used.
getParameters() - Method in class edu.cmu.tetrad.calculator.parser.ExpressionParser
Getter for the field parameters.
getParameters() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
Returns the list of parameters used in the simulation.
getParameters() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the set of parameters.
getParameters() - Method in class edu.cmu.tetrad.sem.SemPm
Getter for the field parameters.
getParameters() - Static method in class edu.cmu.tetrad.util.Params
getParameters.
getParametersEstimationInitializationTemplate() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the parameter estimation initialization template.
getParametersNames() - Method in class edu.cmu.tetrad.util.Parameters
getParametersNames.
getParametersTemplate() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the template for the parameters.
getParameterValue(Edge) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
getParameterValue.
getParameterValue(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Retrieves the value of a parameter in the model.
getParameterValues() - Method in interface edu.cmu.tetrad.algcomparison.utils.HasParameterValues
getParameterValues.
getParameterValues() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph
getParameterValues.
getParameterValues() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
getParameterValues.
getParamName() - Method in class edu.cmu.tetrad.util.ParamDescription
Getter for the field paramName.
getParams() - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field params.
getParams() - Method in class edu.cmu.tetrad.study.performance.ComparisonResult
Getter for the field params.
getParamsWithUnsupportedValueType() - Method in class edu.cmu.tetrad.util.ParamDescriptions
Getter for the field paramsWithUnsupportedValueType.
getParamValue(Node, Node) - Method in interface edu.cmu.tetrad.sem.ISemIm
getParamValue.
getParamValue(Node, Node) - Method in class edu.cmu.tetrad.sem.SemIm
getParamValue.
getParamValue(Parameter) - Method in interface edu.cmu.tetrad.sem.ISemIm
getParamValue.
getParamValue(Parameter) - Method in class edu.cmu.tetrad.sem.SemIm
Retrieves the value associated with the given parameter.
getParent(int, int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the ith parent of the givne node.
getParent(int, int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the ith parent of the givne node.
getParent(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Retrieves the parent of a node at the specified index.
getParent(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the ith parent of the givne node.
getParent(int, int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the ith parent of the givne node.
getParent(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity
Returns the given parent as an IndexedParent.
getParent(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph
Returns the given parent as an IndexedParent.
getParentDim(int, int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the dimension of the given parent for the given node.
getParentDim(int, int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the dimension of the given parent for the given node.
getParentDim(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Retrieves the value of the parent dimension for a given node and parent index.
getParentDim(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the dimension of the given parent for the given node.
getParentDim(int, int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the dimension of the given parent for the given node.
getParentDims(int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the dimensions of the pararents of the given node.
getParentDims(int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the dimensions of the pararents of the given node.
getParentDims(int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Returns a copy of the dimensions of the parent node at the specified index.
getParentDims(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the dimensions of the pararents of the given node.
getParentDims(int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the dimensions of the pararents of the given node.
getParents() - Method in class edu.cmu.tetrad.search.Boss
Returns the map from nodes to the sets of their parents.
getParents() - Method in class edu.cmu.tetrad.search.Sp
Retrieves a mapping of nodes to their parent nodes.
getParents() - Method in interface edu.cmu.tetrad.search.SuborderSearch
The map from nodes to parents resulting from the search.
getParents() - Method in class edu.cmu.tetrad.search.utils.Bes.Arrow
Returns the set of nodes that are in TNeighbors.
getParents() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Returns the parents.
getParents() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
Returns the parents of this function.
getParents(int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the parents of the given node.
getParents(int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the parents of the given node.
getParents(int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Returns an array containing the parents of the specified node.
getParents(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the parents of the given node.
getParents(int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the parents of the given node.
getParents(int) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns the parents of the node at index p.
getParents(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.RevealOutputGraph
Returns the indices of the parent variables for the given variable.
getParents(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Digraph
Returns an array with the indexes of the parents of node i.
getParents(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealOutputGraph
Returns the indices of the parent variables for the given variable.
getParents(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealOutputGraph
Returns the indices of the parent variables for the given variable.
getParents(int) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.OutputGraph
Returns the indices of the parent variables for the given variable.
getParents(Node) - Method in class edu.cmu.tetrad.graph.Dag
Retrieves the list of parent nodes for a given node in the graph.
getParents(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getParents.
getParents(Node) - Method in interface edu.cmu.tetrad.graph.Graph
getParents.
getParents(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
getParents.
getParents(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getParents.
getParents(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns the list of parent nodes for the given node.
getParents(Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns the parents of a node v.
getParents(Node) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the list of parent nodes for the given node.
getParents(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Returns the lagged factors which are into the given factor.
getParents(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Returns the lagged factors which are into the given factor.
getParents(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Returns the lagged factors which are into the given factor.
getParents(String) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Returns the lagged factors which are into the given factor.
getParents(List<Node>, int, Graph, boolean, boolean) - Static method in class edu.cmu.tetrad.graph.Paths
Returns the parents of the node at index p, calculated using Pearl's method.
getParentValue(int, int, int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the given parent value.
getParentValue(int, int, int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the given parent value.
getParentValue(int, int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Retrieves the value of the parent node at the specified row and column index.
getParentValue(int, int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the given parent value.
getParentValue(int, int, int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the given parent value.
getParentValues(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
getParentValues.
getParentValues(int[], int) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
Returns an integer array containing the parent values for a given node index and row index.
getParentValues(int, int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the parents values of the given node.
getParentValues(int, int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the parents values of the given node.
getParentValues(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Returns an integer array containing the parent values for a given node index and row index.
getParentValues(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the parents values of the given node.
getParentValues(int, int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the parents values of the given node.
getParentValues(int, int, int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Computes the parent values for a given node index and row index according to the specified dimensions.
getParentValues(int, int, int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Calculates the parent values at given node and row indices based on the provided dimensions.
getParentValuesForCombination(int, int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Calculates the parent values for a given combination of dimensions.
getParentValuesForCombination(int, int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Calculates the parent values for a given row index based on the provided dimensions.
getPart(int, int, int, int) - Method in class edu.cmu.tetrad.util.Matrix
getPart.
getPath() - Method in interface edu.cmu.tetrad.algcomparison.statistic.utils.SimulationPath
getPath.
getPath() - Method in class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
getPath.
getPath() - Method in class edu.cmu.tetrad.search.utils.PossibleMConnectingPath
Getter for the field path.
getPath(Map<Node, Node>, Node, Node) - Static method in class edu.cmu.tetrad.search.FciOrientDijkstra
Returns the shortest path from the start node to the end node.
getPathBlockingSetRecursive(Graph, Node, Node, Set<Node>, int, Set<Node>) - Static method in class edu.cmu.tetrad.search.SepsetFinder
Finds a set of nodes that blocks all paths from node x to node y in a graph, considering a maximum path length and a set of nodes that must be included in the blocking set.
getPattern() - Method in class edu.cmu.tetrad.data.DelimiterType
Getter for the field pattern.
getPc(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.Mmmb
Getter for the field pc.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianScore
Returns the penalty discount for this score, which is a multiplier on the penalty term of the BIC score.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.search.score.DegenerateGaussianScore
Returns the penalty discount.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.search.score.GicScores
Returns the penalty discount.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the multiplier on the penalty term for this score.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
For BIC score, a multiplier on the penalty term.
getPenaltyDiscount() - Method in interface edu.cmu.tetrad.search.utils.HasPenaltyDiscount
getPenaltyDiscount.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.search.work_in_progress.FasLofs
Getter for the field penaltyDiscount.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Retrieves the penalty discount associated with this entity.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
getPenaltyDiscount.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
getPenaltyDiscount.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
getPenaltyDiscount.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Specialized scoring method for a single parent.
getPenaltyDiscount() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field penaltyDiscount.
getPercent() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Returns the percentage value.
getPercentCorrect() - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Getter for the field percentCorrect.
getPercentCorrect() - Method in interface edu.cmu.tetrad.classify.ClassifierDiscrete
getPercentCorrect.
getPercentCorrect() - Method in class edu.cmu.tetrad.classify.ClassifierMbDiscrete
Getter for the field percentCorrect.
getPercentUnregulated() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Getter for the field percentUnregulated.
getPerms() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Gets the getModel number of bootstrap samples used
getPermutedMatrix() - Method in class edu.cmu.tetrad.search.utils.PermutationMatrixPair
Returns W, permuted rowwise by the permutation passed in through the constructor.
getPi() - Method in class edu.cmu.tetrad.search.Cstar.Record
Retrieves the value of pi.
getPi() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Getter for the field pi.
getPixelDigitalization() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the pixel digitalization error.
getPixelDigitalization() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getPixelDigitalization.
getPolynomial(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialFunction
Returns the polynomial for the given factor.
getPopulationTripleType(Node, Node, Node, IndependenceTest, int, Graph, boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
getPopulationTripleType.
getPopulationTripleType(Node, Node, Node, IndependenceTest, int, Graph, boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
getPopulationTripleType.
getPosition() - Method in class edu.cmu.tetrad.calculator.expression.ConstantExpression
getPosition.
getPosition() - Method in class edu.cmu.tetrad.calculator.expression.EvaluationExpression
getPosition.
getPosition() - Method in interface edu.cmu.tetrad.calculator.expression.Expression
getPosition.
getPosition() - Method in interface edu.cmu.tetrad.calculator.expression.ExpressionDescriptor
getPosition.
getPosition() - Method in class edu.cmu.tetrad.calculator.expression.VariableExpression
getPosition.
getPosterior() - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Returns the posterior probability of the last independence test.
getPosterior() - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
Getter for the field posterior.
getPower() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Returns the power.
getPreamble() - Method in class edu.cmu.tetrad.regression.RegressionResult
getPreamble.
getPrecision() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Gets the getModel precision for the Incomplete Cholesky
getPrecisionAndRecallOnMarkovBlanketGraph(Node, Graph, Graph) - Method in class edu.cmu.tetrad.search.MarkovCheck
Calculates the precision and recall on the Markov Blanket graph for a given node.
getPrecisionAndRecallOnMarkovBlanketGraph2(Node, Graph, Graph) - Method in class edu.cmu.tetrad.search.MarkovCheck
Calculates the precision and recall using LocalGraphConfusion (which calculates the combination of Adjacency and ArrowHead) on the Markov Blanket graph for a given node.
getPrecisionAndRecallOnMarkovBlanketGraphPlotData(Node, Graph, Graph) - Method in class edu.cmu.tetrad.search.MarkovCheck
Calculates the precision and recall on the markov blanket graph plot data.
getPrecisionAndRecallOnMarkovBlanketGraphPlotData2(Node, Graph, Graph) - Method in class edu.cmu.tetrad.search.MarkovCheck
This method calculates the precision and recall of a target node's Markov Blanket in the given estimated graph.
getPredictedValue(double[]) - Method in class edu.cmu.tetrad.regression.RegressionResult
getPredictedValue.
getPrefix(int) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Retrieves a prefix of the size specified by the parameter.
getPrefix(String) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
getPrefix.
getPrefix(String) - Static method in class edu.cmu.tetrad.sem.LargeScaleSimulation
getPrefix.
getPrefix(String) - Static method in class edu.cmu.tetrad.study.performance.Comparison2
getPrefix.
getPriorCount() - Method in class edu.cmu.tetrad.bayes.CptMapCounts
Retrieves the prior count for all cells in the CptMapCounts.
getProb(Proposition) - Method in class edu.cmu.tetrad.bayes.BayesImProbs
Calculates the probability of a given proposition.
getProb(Proposition) - Method in class edu.cmu.tetrad.bayes.CellTableProbs
This method calculates the probability of a given proposition.
getProb(Proposition) - Method in class edu.cmu.tetrad.bayes.DataSetProbs
Calculates the probability of the given assertion in the data set.
getProb(Proposition) - Method in class edu.cmu.tetrad.bayes.DirichletDataSetProbs
Retrieves the probability of the given assertion in the DirichletDataSetProbs.
getProb(Proposition) - Method in class edu.cmu.tetrad.bayes.IntAveDataSetProbs
Calculates the probability of a given assertion.
getProb(Proposition) - Method in class edu.cmu.tetrad.bayes.StoredCellProbs
Calculates the probability for the given proposition assertion.
getProb(Proposition) - Method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
getProb.
getProbability() - Method in class edu.cmu.tetrad.graph.Edge
Getter for the field probability.
getProbability() - Method in class edu.cmu.tetrad.graph.EdgeTypeProbability
Getter for the field probability.
getProbability(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
getProbability.
getProbability(int, int, int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the probability for the given cell in the given CPT.
getProbability(int, int, int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns the probability for the given cell in the given CPT.
getProbability(int, int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Returns the probability for a given node in the table.
getProbability(int, int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns the probability for the given cell in the given CPT.
getProbability(int, int, int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns the probability for the given cell in the given CPT.
getProbs() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
The array of coefP-values for the regression coefficients.
getProbTail(double, double) - Method in class edu.cmu.tetrad.data.GeneralAndersonDarlingTest
getProbTail.
getProperties() - Method in class edu.cmu.tetrad.graph.Edge
Getter for the field properties.
getProperties() - Method in class edu.cmu.tetrad.graph.EdgeTypeProbability
Getter for the field properties.
getProperties() - Method in class edu.cmu.tetrad.util.TetradProperties
getProperties.
getProposition() - Method in class edu.cmu.tetrad.bayes.Evidence
Getter for the field proposition.
getProposition() - Method in class edu.cmu.tetrad.sem.SemEvidence
Getter for the field proposition.
getProtocolDescription() - Static method in class edu.cmu.tetrad.util.NamingProtocol
getProtocolDescription.
getProximalEndpoint(Node) - Method in class edu.cmu.tetrad.graph.Edge
getProximalEndpoint.
getPseudocount(int, int, int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
getPseudocount.
getPurifyTestDescriptions() - Static method in enum class edu.cmu.tetrad.search.utils.BpcTestType
Returns the test type descriptions for the Purify algorithm.
getpValue() - Method in class edu.cmu.tetrad.search.Mimbuild
Getter for the field pValue.
getpValue() - Method in class edu.cmu.tetrad.search.MimbuildTrek
The p-value of the model.
getPValue() - Method in class edu.cmu.tetrad.search.test.ChiSquareTest.Result
Returns the pValue of the result, or NaN if the p-value cannot be determined.
getPValue() - Method in class edu.cmu.tetrad.search.test.IndependenceResult
Returns the p-value of the fact under the null hypothesis of independence.
getPValue() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Returns the probability associated with the most recently executed independence test, of Double.NaN if p value is not meaningful for this test.
getPValue() - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Returns the probability associated with the most recently executed independence test, of Double.NaN if p value is not meaningful for this test.
getPValue() - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Returns the p value associated with the most recent call of isIndependent.
getPValue() - Method in class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
No p-values are available.
getPValue() - Method in class edu.cmu.tetrad.search.utils.DeltaTetradTest
getPValue.
getPValue() - Method in class edu.cmu.tetrad.search.utils.Tetrad
Getter for the field pValue.
getPValue() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Score
getPValue.
getPValue() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.GraphWithPValue
getPValue.
getPValue() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.Score
Returns the P value.
getPValue() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Calculates the p-value for the independence test.
getPValue() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
getPValue.
getPValue() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
Returns the p-value from the last independence test.
getPValue() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
getPValue.
getPValue() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Calculates the p-value for the independence test.
getPValue() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
Needed for IndependenceTest interface.
getPValue() - Method in class edu.cmu.tetrad.sem.DagScorer
getPValue.
getPValue() - Method in interface edu.cmu.tetrad.sem.ISemIm
getPValue.
getPValue() - Method in interface edu.cmu.tetrad.sem.Scorer
getPValue.
getPValue() - Method in class edu.cmu.tetrad.sem.SemIm
getPValue.
getPValue() - Method in class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
getPValue.
getPValue(double) - Method in class edu.cmu.tetrad.search.Lofs
Calculates the p-value using Fisher's exact test.
getPValue(double) - Method in class edu.cmu.tetrad.search.test.ConditionalCorrelationIndependence
Calculates the p-value for a given score using the cumulative distribution function (CDF) of a standard normal distribution.
getPValue(double) - Method in class edu.cmu.tetrad.search.work_in_progress.InverseCorrelation
getPValue.
getPValue(Node, Node) - Method in class edu.cmu.tetrad.search.utils.SepsetMap
Looks up the p-value for {x, y}
getPValue(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Returns the pvalue if the fact of X _||_ Y | Z is within the cache of results for independence fact.
getPValue(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Returns the p-value for x _||_ y | z.
getPValue(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.DagSepsets
 
getPValue(Node, Node, Set<Node>) - Method in interface edu.cmu.tetrad.search.utils.SepsetProducer
Calculates the p-value for a statistical test a _||_ b | sepset.
getPValue(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetsGreedy
Returns the p-value for the independence test between two nodes, given a set of separator nodes.
getPValue(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetsMaxP
Retrieves the p-value from the result of an independence test between two nodes, given a set of separating nodes.
getPValue(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetsMinP
Returns the p-value for the independence test between two nodes, given a set of separator nodes.
getPValue(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetsPossibleMsep
Returns the p-value for the independence test between two nodes, given a set of separator nodes.
getPValue(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetsSet
 
getPValue(Sextad...) - Method in class edu.cmu.tetrad.search.utils.DeltaSextadTest
Takes a list of tetrads for the given data set and returns the chi square value for the test.
getPValue(Tetrad...) - Method in class edu.cmu.tetrad.search.utils.DeltaTetradTest
Returns a p-value for the given list of tetrad.
getPValue(Parameter, int) - Method in interface edu.cmu.tetrad.sem.ISemIm
getPValue.
getPValue(Parameter, int) - Method in class edu.cmu.tetrad.sem.SemIm
getPValue.
getPValueChisq() - Method in class edu.cmu.tetrad.bayes.EmBayesProperties
getPValueChisq.
getPValueDf() - Method in class edu.cmu.tetrad.bayes.EmBayesProperties
Getter for the field pValueDf.
getPValues() - Method in class edu.cmu.tetrad.search.BossLingam
Returns the p-values of the search.
getPValues(List<IndependenceResult>) - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the list of p-values for the given list of results.
getRandomGenerator() - Method in class edu.cmu.tetrad.util.RandomUtil
Getter for the field randomGenerator.
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.NLSemSimulation
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
 
getRandomGraphClass() - Method in interface edu.cmu.tetrad.algcomparison.simulation.Simulation
Retrieves the class of a random graph for the simulation.
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.SingleDatasetSimulation
Returns null, as there is not random graph for this simulation.
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs
 
getRandomGraphClass() - Method in class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
 
getRanks(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
getRanks.
getRawData() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the raw data that is the result of a simulation, in the form of a three-dimensional double array.
getRawData() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getRawData.
getReachableNodes(List<Node>, LegalPairs, List<Node>, List<Node>, Graph, int) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
getReachableNodes.
getRealDistribution(Context) - Method in class edu.cmu.tetrad.calculator.expression.ConstantExpression
getRealDistribution.
getRealDistribution(Context) - Method in class edu.cmu.tetrad.calculator.expression.EvaluationExpression
getRealDistribution.
getRealDistribution(Context) - Method in interface edu.cmu.tetrad.calculator.expression.Expression
getRealDistribution.
getRealDistribution(Context) - Method in class edu.cmu.tetrad.calculator.expression.VariableExpression
getRealDistribution.
getRealEigenvalue(int) - Method in class edu.pitt.csb.mgm.EigenDecomposition
Returns the real part of the ith eigenvalue of the original matrix.
getRealEigenvalues() - Method in class edu.pitt.csb.mgm.EigenDecomposition
Gets a copy of the real parts of the eigenvalues of the original matrix.
getReason() - Method in class edu.cmu.tetrad.search.utils.GraphSearchUtils.LegalMagRet
Returns the reason why the graph is not a legal MAG, if not.
getReason() - Method in class edu.cmu.tetrad.search.utils.GraphSearchUtils.LegalPagRet
Returns the reason why the graph is not a legal PAG, if not.
getRecords() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Getter for the field records.
getRecords(DataSet, List<Node>, List<Node>, int, String) - Method in class edu.cmu.tetrad.search.Cstar
Returns records for a set of variables with expected number of false positives bounded by q.
getReferencedNodes(Node) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves a set of referenced nodes for the given node.
getReferencedParameters(Node) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the set of referenced parameters from a given node.
getReferencingNodes(Node) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the set of referencing nodes for a given node.
getReferencingNodes(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Returns a set of nodes that reference the given parameter.
getRegressorNames() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
The variables.
getRegressorNames() - Method in class edu.cmu.tetrad.regression.RegressionResult
Getter for the field regressorNames.
getRemap() - Method in class edu.cmu.tetrad.data.DiscreteDiscretizationSpec
Getter for the field remap.
getRemoves() - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Return removes
getReport() - Method in class edu.cmu.tetrad.sem.GeneralizedSemEstimator
Retrieves the report generated by the GeneralizedSemEstimator.
getRequired() - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
Getter for the field required.
getResamplingDataset(DataSet, int) - Static method in class edu.cmu.tetrad.data.DataTransforms
getResamplingDataset.
getResamplingDataset(DataSet, int, RandomGenerator) - Static method in class edu.cmu.tetrad.data.DataTransforms
Get dataset sampled without replacement.
getResidual() - Method in class edu.cmu.tetrad.search.FactorAnalysis
Returns the matrix of residuals.
getResiduals() - Method in class edu.cmu.tetrad.regression.RegressionResult
getResiduals.
getResiduals() - Method in class edu.cmu.tetrad.search.utils.TsUtils.VarResult
Getter for the field residuals.
getResidualsWithoutFirstRegressor() - Method in class edu.cmu.tetrad.regression.RegressionDataset
getResidualsWithoutFirstRegressor.
getResultGraph() - Method in class edu.cmu.tetrad.study.performance.ComparisonResult
Getter for the field resultGraph.
getResults(boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
After the generateResults method has been called, this method returns the results for the Markov or dependency check, depending on the value of the indep parameter.
getResultsTable() - Method in class edu.cmu.tetrad.regression.RegressionResult
getResultsTable.
getResultType() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field resultType.
getRho() - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Getter for the field rho.
getRmsea() - Method in interface edu.cmu.tetrad.sem.ISemIm
getRmsea.
getRmsea() - Method in class edu.cmu.tetrad.sem.SemIm
getRmsea.
getRootElement(File) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
getRootElement.
getRow(boolean[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
Returns the row for the given combination of parent values.
getRow(int) - Method in class edu.cmu.tetrad.util.Matrix
getRow.
getRowCounts(List<DataModel>) - Static method in class edu.cmu.tetrad.util.MultidataUtils
getRowCounts.
getRowIndex(int, int[]) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns a row index.
getRowIndex(int, int[]) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
getRowIndex.
getRowIndex(int, int[]) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Returns the row index corresponding to the given node index and combination of parent values.
getRowIndex(int, int[]) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
getRowIndex.
getRowIndex(int, int[]) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
getRowIndex.
getRowPerm() - Method in class edu.cmu.tetrad.search.utils.PermutationMatrixPair
Getter for the field rowPerm.
getRowPseudocount(int, int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
getRowPseudocount.
getRows() - Method in class edu.cmu.tetrad.search.test.ConditionalCorrelationIndependence
Retrieves the list of row indices currently set for the analysis.
getRows() - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Returns the rows used for the test.
getRows() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalCorrelation
Returns the number of orthogonal functions used to do the calculations.
getRows() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Returns the rows used in the test.
getRows() - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Returns the rows used in the test.
getRows() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Returns the rows used in the test.
getRows() - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Retrieves the list of rows to use for the test.
getRows() - Method in class edu.cmu.tetrad.search.test.Kci
Returns the rows used in the test.
getRows() - Method in interface edu.cmu.tetrad.search.test.RowsSettable
Gets the rows to use for the test.
getRows() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Retrieves the array of row indices.
getRows(double[], double[], double, double) - Static method in class edu.cmu.tetrad.util.StatUtils
getRows.
getRows(double[], double, double) - Static method in class edu.cmu.tetrad.util.StatUtils
getRows.
getRowValues(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
getRowValues.
getRuntime() - Method in class edu.cmu.tetrad.search.work_in_progress.Ion
Getter for the field runtime.
getS() - Method in class edu.cmu.tetrad.search.FastIca.IcaResult
Returns the estimated source matrix.
getSampleCovar() - Method in class edu.cmu.tetrad.sem.DagScorer
Getter for the field sampleCovar.
getSampleCovar() - Method in interface edu.cmu.tetrad.sem.Scorer
getSampleCovar.
getSampleCovar() - Method in class edu.cmu.tetrad.sem.SemIm
getSampleCovar.
getSamplePrior() - Method in class edu.cmu.tetrad.search.score.BdeuScore
Returns the sample prior.
getSamplePrior() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Retrieves the prior value of the sample.
getSamplePrior() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Calculates and returns the sample prior value.
getSamplePrior() - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Retrieves the prior probability assigned to the sample.
getSamplePrior() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field samplePrior.
getSampleSampleVariability() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the sample to sample variability, which is the standard deviation of a normal distribution with mean 0 from which errors in measured expression levels due to the microarray being used for measurement are drawn.
getSampleSampleVariability() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getSampleSampleVariability.
getSampleSize() - Method in class edu.cmu.tetrad.bayes.BayesProperties
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
The size of the sample used to calculated this covariance matrix.
getSampleSize() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
The size of the sample used to calculated this covariance matrix.
getSampleSize() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
The size of the sample used to calculated this covariance matrix.
getSampleSize() - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Retrieves the sample size used in the covariance matrix.
getSampleSize() - Method in class edu.cmu.tetrad.data.SplitCasesSpec
Getter for the field sampleSize.
getSampleSize() - Method in interface edu.cmu.tetrad.search.IndependenceTest
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.BasisFunctionBicScore
Retrieves the sample size from the underlying BIC score component.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.BdeScore
Returns the sample size of the data set.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.BdeuScore
Returns the sample size of the data.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianScore
Returns the sample size of the data.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.DegenerateGaussianScore
The sample size of the data.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.EbicScore
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.GicScores
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.GraphScore
getSampleSize.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.ImagesScore
The sample size of the data.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.IndTestScore
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.MvpScore
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.PoissonPriorScore
Returns the sample size.
getSampleSize() - Method in interface edu.cmu.tetrad.search.score.Score
The sample size of the data.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.score.ZsbScore
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Returns the sample size used in the covariance matrix.
getSampleSize() - Method in class edu.cmu.tetrad.search.test.Kci
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Retrieves the sample size of the data set.
getSampleSize() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Retrieves the sample size of the covariance matrix.
getSampleSize() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Retrieves the current sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Retrieves the current sample size.
getSampleSize() - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Retrieves the sample size used in the score computation.
getSampleSize() - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
The sample size of the data.
getSampleSize() - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
The sample size of the data.
getSampleSize() - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
The sample size of the data.
getSampleSize() - Method in class edu.cmu.tetrad.search.work_in_progress.MnlrScore
Returns the sample size.
getSampleSize() - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Getter for the field sampleSize.
getSampleSize() - Method in class edu.cmu.tetrad.sem.DagScorer
getSampleSize.
getSampleSize() - Method in interface edu.cmu.tetrad.sem.ISemIm
getSampleSize.
getSampleSize() - Method in interface edu.cmu.tetrad.sem.Scorer
getSampleSize.
getSampleSize() - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field sampleSize.
getSampleSize() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
Getter for the field sampleSize.
getSampleSize() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field sampleSize.
getScaledBHat(PermutationMatrixPair) - Static method in class edu.cmu.tetrad.search.IcaLingD
Returns the BHat matrix, permuted to the variable order of the original data and scaled so that the diagonal consists only of 1's.
getScaledBHats(Matrix) - Method in class edu.cmu.tetrad.search.IcaLingD
Performs the LiNG-D algorithm given a W matrix, which needs to be discovered elsewhere.
getScaledRocPlot() - Method in class edu.cmu.tetrad.util.RocCalculator
getScaledRocPlot.
getScalingFactor() - Method in class edu.cmu.tetrad.search.test.ConditionalCorrelationIndependence
Retrieves the kernel scaling factor.
getScore() - Method in class edu.cmu.tetrad.search.Boss
Returns the score being used for the search.
getScore() - Method in class edu.cmu.tetrad.search.score.ScoredGraph
Returns the score.
getScore() - Method in class edu.cmu.tetrad.search.Sp
Retrieves the score associated with this object.
getScore() - Method in interface edu.cmu.tetrad.search.SuborderSearch
The score being used.
getScore() - Method in class edu.cmu.tetrad.search.test.IndependenceResult
Returns the score of the test, which is alpha - p if the test returns a p-value or else a bump if the test is based on a score.
getScore() - Method in class edu.cmu.tetrad.search.utils.DagSepsets
Returns the score of the object.
getScore() - Method in interface edu.cmu.tetrad.search.utils.SepsetProducer
Returns the score of the object.
getScore() - Method in class edu.cmu.tetrad.search.utils.SepsetsGreedy
Calculates the score for the given Sepsets object.
getScore() - Method in class edu.cmu.tetrad.search.utils.SepsetsMaxP
Calculates the score for the given Sepsets object.
getScore() - Method in class edu.cmu.tetrad.search.utils.SepsetsMinP
Calculates the score for the given Sepsets object.
getScore() - Method in class edu.cmu.tetrad.search.utils.SepsetsPossibleMsep
Returns the score of the object.
getScore() - Method in class edu.cmu.tetrad.search.utils.SepsetsSet
Returns the score of the object.
getScore() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Score
getScore.
getScore() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.Score
Returns the score.
getScore() - Method in interface edu.cmu.tetrad.sem.ISemIm
getScore.
getScore() - Method in class edu.cmu.tetrad.sem.SemIm
The value of the maximum likelihood function for the getModel the model (Bollen 107).
getScore() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field score.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.BasisFunctionBicScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.BdeuScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.ConditionalGaussianBicScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.DegenerateGaussianBicScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.DiscreteBicScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.EbicScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.FisherZScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.GicScores
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.MagDgBicScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.MSeparationScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.MVPBicScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.PoissonPriorScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.PositiveCorrScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in interface edu.cmu.tetrad.algcomparison.score.ScoreWrapper
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.SemBicScore
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.SemBicScoreDeterministic
Returns true, iff x and y are independent, conditional on z for the given data set.
getScore(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.score.ZhangShenBoundScore
Calculates the score based on the given data set and parameters.
getScore(Graph) - Method in class edu.cmu.tetrad.search.SvarFges
Returns the score of the given DAG.
getScore(Graph) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
getScore.
getScore(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Calculates and returns the score of the provided Directed Acyclic Graph (DAG).
getScore(IndependenceResult) - Method in class edu.cmu.tetrad.search.test.Kci
Returns alpha - p.
getScoreCount(Node, Set<Node>) - Method in class edu.cmu.tetrad.bayes.BdeMetricCache
This is just for testing the operation of the inner class and the map from nodes and parent sets to scores.
getScoreFact(int, int[], List<Node>) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
getScoreFact.
getScoreFact(Node, List<Node>) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
getScoreFact.
getScoreParameters(Algorithm) - Static method in class edu.cmu.tetrad.util.Params
getScoreParameters.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.DirectLingam
Retrieves the ScoreWrapper object associated with this DirectLingam instance.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Retrieves the ScoreWrapper object associated with this class.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Retrieves the ScoreWrapper object associated with this class.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Returns the score wrapper.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Retrieves the score wrapper object.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Returns the score wrapper.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Boss
Returns the score wrapper.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossLingam
Returns the score wrapper.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Returns the score wrapper.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges
Returns the score wrapper.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMb
Returns the score wrapper.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Returns the score wrapper.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.RestrictedBoss
Returns the score wrapper.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Sp
Returns the score wrapper.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Retrieves the ScoreWrapper associated with this algorithm.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossDumb
Retrieves the ScoreWrapper object associated with this method.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPag
Retrieves the ScoreWrapper object associated with this method.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Retrieves the ScoreWrapper associated with this instance.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Retrieves the ScoreWrapper object associated with this method.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
Retrieves the ScoreWrapper object associated with this method.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Retrieves the ScoreWrapper object associated with this algorithm.
getScoreWrapper() - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Retrieves the ScoreWrapper object associated with this algorithm.
getScoreWrapper() - Method in interface edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper
Returns the score wrapper.
getSd() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Returns the standard deviation.
getSe() - Method in class edu.cmu.tetrad.regression.RegressionResult
Getter for the field se.
getSecond() - Method in class edu.cmu.tetrad.graph.NodePair
Getter for the field second.
getSecond() - Method in class edu.cmu.tetrad.graph.OrderedPair
Getter for the field second.
getSecondEdge() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move
Getter for the field secondEdge.
getSelectedIndices() - Method in class edu.cmu.tetrad.data.BoxDataSet
getSelectedIndices.
getSelectedIndices() - Method in interface edu.cmu.tetrad.data.DataSet
getSelectedIndices.
getSelectedIndices() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getSelectedIndices.
getSelectedModel() - Method in class edu.cmu.tetrad.data.DataModelList
Getter for the field selectedModel.
getSelectedVariableNames() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
getSelectedVariableNames.
getSelectedVariableNames() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
getSelectedVariableNames.
getSelectedVariableNames() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
getSelectedVariableNames.
getSelectedVariableNames() - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Retrieves a list of names of the currently selected variables.
getSelectedVariables() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getSelectedVariables.
getSelection(int[]) - Method in class edu.cmu.tetrad.util.Vector
viewSelection.
getSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.CorrelationMatrix
Returns a submatrix based on the specified rows and columns.
getSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Returns a submatrix based on the specified rows and columns.
getSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Returns a submatrix based on the specified rows and columns.
getSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Returns a submatrix based on the specified rows and columns.
getSelection(int[], int[]) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Returns a submatrix based on the specified rows and columns.
getSelection(int[], int[]) - Method in class edu.cmu.tetrad.util.Matrix
getSelection.
getSelection(int[], int[], int[]) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
getSelection.
getSelectionBias() - Method in class edu.cmu.tetrad.data.ContinuousVariable
 
getSelectionBias() - Method in class edu.cmu.tetrad.data.DiscreteVariable
 
getSelectionBias() - Method in class edu.cmu.tetrad.graph.GraphNode
Returns true if this node is selected as a bias node.
getSelectionBias() - Method in interface edu.cmu.tetrad.graph.Node
Returns the selection bias status for this node.
getSelfLoopCoef() - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Getter for the field selfLoopCoef.
getSelfLoopCoefs(DataSet) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
getSelfLoopCoefs.
getSemIm() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Getter for the field semIm.
getSemIm() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Getter for the field semIm.
getSemIm() - Method in class edu.cmu.tetrad.sem.ParamConstraint
Getter for the field semIm.
getSemIm() - Method in class edu.cmu.tetrad.sem.SemEvidence
Getter for the field semIm.
getSemIm() - Method in class edu.cmu.tetrad.sem.SemProposition
Retrieves the SemIm object associated with this SemProposition.
getSemIm() - Method in class edu.cmu.tetrad.sem.SemUpdater
Getter for the field semIm.
getSemIm(Element) - Static method in class edu.cmu.tetrad.sem.SemXmlParser
Takes an xml representation of a SEM IM and reinstantiates the IM
getSemPm() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Getter for the field semPm.
getSemPm() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Getter for the field semPm.
getSemPm() - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
getSemPm.
getSemPm() - Method in interface edu.cmu.tetrad.sem.ISemIm
getSemPm.
getSemPm() - Method in class edu.cmu.tetrad.sem.SemEstimator
Getter for the field semPm.
getSemPm() - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbs
Getter for the field semPm.
getSemPm() - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field semPm.
getSemPm() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
Getter for the field semPm.
getSeparatedPairs() - Method in class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
getSeparatedPairs.
getSeparators(Node[], Map<Node, Set<Node>>) - Static method in class edu.cmu.tetrad.bayes.GraphTools
Calculate separator sets in clique tree.
getSepset() - Method in class edu.cmu.tetrad.search.work_in_progress.Dci
Gets the resulting sepsets
getSepset() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Getter for the field sepset.
getSepset(Node, Node, boolean, IndependenceTest, int) - Method in class edu.cmu.tetrad.graph.Paths
Finds a sepset for x and y, if there is one; otherwise, returns null.
getSepset(Node, Node, int) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Retrieves the set of nodes that form the sepset between two given nodes.
getSepset(Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.DagSepsets
Retrieves the sepset, which is the set of common neighbors between two given nodes.
getSepset(Node, Node, int) - Method in interface edu.cmu.tetrad.search.utils.SepsetProducer
Retrieves the sepset, which is the set of common neighbors between two given nodes.
getSepset(Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsGreedy
Retrieves the sepset (separating set) between two nodes, or null if no such sepset is found.
getSepset(Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsMaxP
Retrieves the sepset (separating set) between two nodes which contains a set of nodes.
getSepset(Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsMinP
Retrieves the sepset (separating set) between two nodes, or null if no such sepset is found.
getSepset(Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsPossibleMsep
Retrieves the separation set (sepset) between two nodes.
getSepset(Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsSet
Retrieves the sepset between two nodes.
getSepset(Node, Node, IndependenceTest) - Method in class edu.cmu.tetrad.graph.Dag
Returns the sepset between two given nodes in the graph.
getSepset(Node, Node, IndependenceTest) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Returns the set of nodes that form the separating set between two given nodes.
getSepset(Node, Node, IndependenceTest) - Method in interface edu.cmu.tetrad.graph.Graph
Returns the set of nodes that form the separating set between two given nodes.
getSepset(Node, Node, IndependenceTest) - Method in class edu.cmu.tetrad.graph.LagGraph
Returns the set of nodes that form the separating set between two given nodes.
getSepset(Node, Node, IndependenceTest) - Method in class edu.cmu.tetrad.graph.SemGraph
Returns the set of nodes that form the separating set between two given nodes.
getSepset(Node, Node, IndependenceTest) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Retrieves the sepset of two nodes in the graph.
getSepset(IndependenceTest, Node, Node) - Method in class edu.cmu.tetrad.search.utils.PossibleMsepFci
Getter for the field sepset.
getSepsetContaining(Node, Node, Set<Node>, int) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Retrieves the set of nodes that form the sepset between two given nodes.
getSepsetContaining(Node, Node, Set<Node>, int) - Method in class edu.cmu.tetrad.graph.Paths
Retrieves a sepset (a set of nodes) between two given nodes.
getSepsetContaining(Node, Node, Set<Node>, int) - Method in class edu.cmu.tetrad.search.utils.DagSepsets
Returns the sepset containing nodes 'a' and 'b' that also contains all the nodes in the given set 's'.
getSepsetContaining(Node, Node, Set<Node>, int) - Method in interface edu.cmu.tetrad.search.utils.SepsetProducer
Retrieves a sepset containing nodes in s from the given set of nodes.
getSepsetContaining(Node, Node, Set<Node>, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsGreedy
Retrieves a sepset (separating set) between two nodes containing a set of nodes, containing the nodes in s, or null if no such sepset is found.
getSepsetContaining(Node, Node, Set<Node>, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsMaxP
Retrieves a sepset (separating set) between two nodes containing a set of nodes containing the nodes in s, or null if no such sepset is found.
getSepsetContaining(Node, Node, Set<Node>, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsMinP
Retrieves a sepset (separating set) between two nodes containing a set of nodes containing the nodes in s, or null if no such sepset is found.
getSepsetContaining(Node, Node, Set<Node>, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsPossibleMsep
Retrieves the separation set (sepset) between two nodes i and k that contains a given set of nodes s.
getSepsetContaining(Node, Node, Set<Node>, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsSet
Retrieves the sepset for a and b, where we are expecting this sepset to contain all the nodes in s.
getSepsetContainingGreedy(Graph, Node, Node, Set<Node>, IndependenceTest, int) - Static method in class edu.cmu.tetrad.search.SepsetFinder
Returns the sepset that contains the greedy test for variables x and y in the given graph.
getSepsetContainingMaxPHybrid(Graph, Node, Node, Set<Node>, IndependenceTest, int) - Static method in class edu.cmu.tetrad.search.SepsetFinder
Returns the set of nodes that act as a separating set between two given nodes (x and y) in a graph.
getSepsetContainingMinPHybrid(Graph, Node, Node, Set<Node>, IndependenceTest, int) - Static method in class edu.cmu.tetrad.search.SepsetFinder
Returns the sepset containing the minimum p-value for the given variables x and y.
getSepsetPathBlockingOutOfX(Graph, Node, Node, IndependenceTest, int, int, boolean, Set<Node>) - Static method in class edu.cmu.tetrad.search.SepsetFinder
Calculates the sepset path blocking out-of operation for a given pair of nodes in a graph.
getSepsets() - Method in class edu.cmu.tetrad.search.Cfci
Returns the map from nodes to their sepsets.
getSepsets() - Method in class edu.cmu.tetrad.search.Cpc
Returns a map for x _||_ y | z1,..,zn from {x, y} to {z1,...,zn}.
getSepsets() - Method in class edu.cmu.tetrad.search.Fas
Returns the sepsets that were discovered in the search.
getSepsets() - Method in class edu.cmu.tetrad.search.Fasd
Returns the map of node pairs to sepsets from the search.
getSepsets() - Method in class edu.cmu.tetrad.search.Fci
Returns the sepset map from FAS.
getSepsets() - Method in class edu.cmu.tetrad.search.FciMax
Retrieves the map from variable pairs to sepsets from the FAS search.
getSepsets() - Method in interface edu.cmu.tetrad.search.IFas
Returns the sepset map discovered during search--that is, the map from node pairs to the sepsets used in the search to remove the corresponding edges from the complete graph.
getSepsets() - Method in class edu.cmu.tetrad.search.Pc
Returns the sepset map from the most recent search.
getSepsets() - Method in class edu.cmu.tetrad.search.Pcd
Getter for the field sepsets.
getSepsets() - Method in class edu.cmu.tetrad.search.Rfci
Returns the map from node pairs to sepsets found in search.
getSepsets() - Method in class edu.cmu.tetrad.search.SvarFas
Returns a map for x _||_ y | Z from {x, y} to Z.
getSepsets() - Method in class edu.cmu.tetrad.search.SvarFci
Returns the map from node pairs to sepsets.
getSepsets() - Method in class edu.cmu.tetrad.search.work_in_progress.FasFdr
Returns a map for x _||_ y | z1,...,zn of {x, y} to {z1,...,zn},
getSet(Node, Node) - Method in class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
Retrieves the set of all condioning sets for {x, y} or null if no such set was ever set
getSetType() - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns type of conditioning sets to use in the Markov check.
getShat() - Method in class edu.cmu.tetrad.sem.Ricf.RicfResult
Retrieves the shat matrix.
getShd() - Method in class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Returns the adjacency precision.
getShortDescription() - Method in class edu.cmu.tetrad.util.ParamDescription
Getter for the field shortDescription.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Returns the short name of the simulation.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Returns the short name of the simulation.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Returns the short name of the simulation.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1
Returns the short name of the simulation.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation
Returns the short name of the simulation.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
Returns the short name of the simulation.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Returns the short name of the simulation.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.NLSemSimulation
Returns the short name of the simulation.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Returns the short name of the simulation.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
Returns the short name of the simulation.
getShortName() - Method in interface edu.cmu.tetrad.algcomparison.simulation.Simulation
Returns the short name of the simulation.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
Returns the short name of the simulation.
getShortName() - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
Returns the short name of the simulation.
getShuffledVariables() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
getShuffledVariables.
getSignature() - Method in interface edu.cmu.tetrad.calculator.expression.ExpressionDescriptor
getSignature.
getSignature() - Method in interface edu.cmu.tetrad.calculator.expression.ExpressionSignature
getSignature.
getSignificance() - Method in interface edu.cmu.tetrad.search.utils.TetradTest
getSignificance.
getSignificance() - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
getSignificance.
getSignificance() - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
getSignificance.
getSignificance() - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
getSignificance.
getSignificantModels() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
Getter for the field significantModels.
getSimulation() - Method in class edu.cmu.tetrad.algcomparison.algorithm.ExternalAlgorithm
Getter for the field simulation.
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
 
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
 
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
 
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1
 
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation
 
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
 
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
 
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.NLSemSimulation
 
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
 
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
 
getSimulationClass() - Method in interface edu.cmu.tetrad.algcomparison.simulation.Simulation
Returns the class of the simulation.
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.SingleDatasetSimulation
Retrieves the class of the simulation.
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
 
getSimulationClass() - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
 
getSimulationClass() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs
 
getSimulationClass() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph
 
getSimulationClass() - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
 
getSimulationClass() - Method in class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs
 
getSimulationClass() - Method in class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
 
getSimulations() - Method in class edu.cmu.tetrad.algcomparison.simulation.Simulations
Returns the list of simulations.
getSimulator() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
Getter for the field simulator.
getSingleCategory(int) - Method in class edu.cmu.tetrad.bayes.Proposition
getSingleCategory.
getSize() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
getSize.
getSize() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
getSize.
getSize() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
getSize.
getSize() - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Retrieves the size of the matrix.
getSize() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.RevealOutputGraph
getSize.
getSize() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealOutputGraph
getSize.
getSize() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealOutputGraph
getSize.
getSize() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Returns the # nodes in this graph
getSize() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Returns # rows ( == # columns) of this matrix
getSize() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.OutputGraph
Returns the number of variables over which the graph is defined.
getSize() - Method in class edu.cmu.tetrad.util.Point
getSize.
getSkeleton() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
getSkeleton.
getSmallestSubset(Node, Node, Set<Node>, Set<Node>, Graph, boolean) - Static method in class edu.cmu.tetrad.search.SepsetFinder
Finds a smallest subset S of blocking that renders two nodes x and y conditionally d-separated conditional on S in the given graph.
getSoCalledPoissonShocks(int) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
getSoCalledPoissonShocks.
getSolver() - Method in class edu.pitt.csb.mgm.EigenDecomposition
Gets a solver for finding the A × X = B solution in exact linear sense.
getSplitNames() - Method in class edu.cmu.tetrad.data.SplitCasesSpec
Getter for the field splitNames.
getSquaredDistance(OrderedPair<Node>) - Method in class edu.cmu.tetrad.search.IdaCheck
Calculates the squared distance of the true total effect to the [min, max] IDA effect range of the given (x, y) node pair, for x predicting y.
getSquaredMaxTrueDist(OrderedPair<Node>) - Method in class edu.cmu.tetrad.search.IdaCheck
Returns the squared difference between the maximum total effect and the true total effect for the given pair of nodes.
getSquaredMinTrueDistance(OrderedPair<Node>) - Method in class edu.cmu.tetrad.search.IdaCheck
Returns the squared difference between the minimum total effect and the true total effect for the given pair of nodes.
getSquareRoot() - Method in class edu.pitt.csb.mgm.EigenDecomposition
Computes the square-root of the matrix.
getSs() - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Getter for the field ss.
getStableBHats() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingD
Retrieves the list of stable B matrices generated by the algorithm.
getStableGraphs() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingD
Retrieves the list of stable graphs generated by the algorithm.
getStandardError(Parameter, int) - Method in interface edu.cmu.tetrad.sem.ISemIm
getStandardError.
getStandardError(Parameter, int) - Method in class edu.cmu.tetrad.sem.SemIm
getStandardError.
getStartIm() - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbsParams
Getter for the field startIm.
getStartingValue() - Method in class edu.cmu.tetrad.sem.Parameter
Getter for the field startingValue.
getStartsWithParameterEstimationInitializationTemplate(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the initialization template for parameter estimation based on the provided starting string.
getStartsWithParameterTemplate(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
getStartsWithParameterTemplate.
getStatistics() - Method in class edu.cmu.tetrad.algcomparison.statistic.Statistics
Return the list of statistics.
getStats() - Method in class edu.cmu.tetrad.search.work_in_progress.Ion
Summarizes time and hitting set time and size information for latex
getStatsListTable(Graph, Graph) - Static method in class edu.cmu.tetrad.algcomparison.CompareTwoGraphs
Returns a string representing a table of statistics that can be printed.
getStatsListTable(Graph, Graph, DataModel, long) - Static method in class edu.cmu.tetrad.algcomparison.CompareTwoGraphs
Returns a string representing a table of statistics that can be printed.
getStdDev(Node, Matrix) - Method in interface edu.cmu.tetrad.sem.ISemIm
getStdDev.
getStdDev(Node, Matrix) - Method in class edu.cmu.tetrad.sem.SemIm
getStdDev.
getStdErrors() - Method in class edu.cmu.tetrad.sem.SemStdErrorEstimator
getStdErrors.
getStdErrs() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
The array of standard errors for the regression coefficients.
getStep() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Returns the getModel step.
getStepsGenerated() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the number of steps generated.
getStepsGenerated() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getStepsGenerated.
getStretch() - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbsParams
Getter for the field stretch.
getString(String) - Method in class edu.cmu.tetrad.util.Parameters
Returns the string value of the given parameter, looking up its default in the ParamDescriptions map.
getString(String, String) - Method in class edu.cmu.tetrad.util.Parameters
Returns the string value of the given parameter, using the given default.
getStructurePrior() - Method in class edu.cmu.tetrad.search.score.BdeuScore
Retrieves the structure prior associated with this BdeuScore object.
getStructurePrior() - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the structure prior for this score.
getStructurePrior() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Retrieves the value of the structure prior.
getStructurePrior() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Retrieves the prior probability of the given structure.
getStructurePrior() - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Retrieves the prior value assigned to the structure.
getStructurePrior() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field structurePrior.
getStructurePrior(int) - Method in class edu.cmu.tetrad.search.score.MvpLikelihood
Returns the structure prior.
getStructurePrior(int) - Method in class edu.cmu.tetrad.search.work_in_progress.MnlrLikelihood
Returns the structur prior for k parents.
getSubCorrMatrix(String[]) - Method in class edu.cmu.tetrad.data.CorrelationMatrix
getSubCorrMatrix.
getSubFunction(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
getSubFunction.
getSubmatrix(int[]) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
getSubmatrix.
getSubmatrix(int[]) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
getSubmatrix.
getSubmatrix(int[]) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
getSubmatrix.
getSubmatrix(int[]) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Returns a submatrix of the covariance matrix, including only the specified variables.
getSubmatrix(int[], int[]) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
getSubmatrix.
getSubmatrix(String[]) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
getSubmatrix.
getSubmatrix(String[]) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
getSubmatrix.
getSubmatrix(String[]) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
getSubmatrix.
getSubmatrix(String[]) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Returns a submatrix of the covariance matrix, including only the specified variables.
getSubmatrix(List<String>) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
getSubmatrix.
getSubmatrix(List<String>) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
getSubmatrix.
getSubmatrix(List<String>) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
getSubmatrix.
getSubmatrix(List<String>) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Returns a submatrix of the covariance matrix, including only the specified variables.
getSubMatrix(int[], int[]) - Method in interface edu.cmu.tetrad.data.Covariances
Returns a submatrix of the covariance matrix for the given rows and columns.
getSubMatrix(int[], int[]) - Method in class edu.cmu.tetrad.data.CovariancesDoubleForkJoin
getSubMatrix.
getSupportedEvents() - Method in class edu.cmu.tetrad.util.DefaultTetradLoggerConfig
getSupportedEvents.
getSupportedEvents() - Method in class edu.cmu.tetrad.util.TetradLogger.EmptyConfig
getSupportedEvents.
getSupportedEvents() - Method in interface edu.cmu.tetrad.util.TetradLoggerConfig
Retrieves the list of supported events.
getSupportLowerBound() - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Returns the lower bound of the support for the distribution.
getSupportUpperBound() - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Returns the upper bound of the support for the distribution.
getT() - Method in class edu.cmu.tetrad.regression.RegressionResult
Getter for the field t.
getTarget() - Method in class edu.cmu.tetrad.data.Histogram
Getter for the field target.
getTarget() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
The target.
getTargetNode() - Method in class edu.cmu.tetrad.data.Histogram
getTargetNode.
getTargets() - Method in class edu.cmu.tetrad.search.PcMb
Return the targets of the most recent search.
getTargetVariable() - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Getter for the field targetVariable.
getTerm(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.Polynomial
Returns the coefficient.
getTest() - Method in class edu.cmu.tetrad.search.PcMb
Returns the test used in search.
getTest() - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Retrieves the IndependenceTest object used by the strategy.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.BasisFunctionBicTest
Returns an instance of IndependenceTest for the Basis Function BIC test.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.BdeuTest
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.CciTest
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.ChiSquare
Retrieves an instance of the IndependenceTest interface that performs a Chi Square Test for independence.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.ConditionalGaussianLRT
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.DegenerateGaussianLRT
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.DiscreteBicTest
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.FisherZ
Gets an independence test based on the given data model and parameters.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.GICScoreTests
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.GSquare
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in interface edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.Kci
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.MagSemBicTest
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.Mnlrlrt
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.MSeparationTest
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.MultinomialLogisticRegressionWald
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.Mvplrt
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.PoissonPriorTest
Returns an instance of IndependenceTest for the Poisson Prior test.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.PositiveCorr
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.ProbabilisticTest
Returns true iff x and y are independent conditional on z for the given data set.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.SemBicDTest
Retrieves an IndependenceTest object for testing independence against a given data set and parameters.
getTest(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.independence.SemBicTest
Returns an instance of IndependenceTest for the SEM BIC test.
getTestData() - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Returns the test data being used.
getTestDescriptions() - Static method in enum class edu.cmu.tetrad.search.utils.BpcTestType
Returns the test type descriptions for the BuildPureClusters algorithm.
getTestParameters(Algorithm) - Static method in class edu.cmu.tetrad.util.Params
getTestParameters.
getTestType() - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
getTestType.
getTetradLoggerConfig() - Method in class edu.cmu.tetrad.util.TetradLoggerEvent
getTetradLoggerConfig.
getThr() - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Getter for the field thr.
getTier(int) - Method in class edu.cmu.tetrad.data.Knowledge
getTier.
getTimeLagGraph() - Method in class edu.cmu.tetrad.graph.Dag
getTimeLagGraph.
getTimeLagGraph() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getTimeLagGraph.
getTimeLagGraph() - Method in interface edu.cmu.tetrad.graph.Graph
getTimeLagGraph.
getTimeLagGraph() - Method in class edu.cmu.tetrad.graph.LagGraph
getTimeLagGraph.
getTimeLagGraph() - Method in class edu.cmu.tetrad.graph.SemGraph
getTimeLagGraph.
getTimeLagGraph() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns the TimeLagGraph object.
getTimes() - Method in class edu.cmu.tetrad.search.Boss
Returns the times.
getTimeSteps() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the time steps that will be stored in the simulation.
getTimeSteps() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
getTimeSteps.
getTn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.AdjacencyConfusion
Returns the true negative count.
getTn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
True negatives.
getTn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.BidirectedConfusion
Returns the number of true negatives.
getTn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.LocalGraphConfusion
Retrieves the value of true negatives (TN) from the LocalGraphConfusion object.
getTn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.OrientationConfusion
Getter for the field tn.
getTnc() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
True Negatives for common edges.
getTNeighbors() - Method in class edu.cmu.tetrad.search.utils.Bes.Arrow
Returns the set of nodes that are in TNeighbors.
getTo() - Method in class edu.cmu.tetrad.data.KnowledgeEdge
Getter for the field to.
getToken() - Method in class edu.cmu.tetrad.calculator.expression.ConstantExpression
getToken.
getToken() - Method in class edu.cmu.tetrad.calculator.expression.EvaluationExpression
getToken.
getToken() - Method in interface edu.cmu.tetrad.calculator.expression.Expression
getToken.
getToken() - Method in interface edu.cmu.tetrad.calculator.expression.ExpressionDescriptor
getToken.
getToken() - Method in class edu.cmu.tetrad.calculator.expression.VariableExpression
getToken.
getTokenAt(int, int) - Method in class edu.cmu.tetrad.util.TextTable
getTokenAt.
getTokenString() - Method in class edu.cmu.tetrad.calculator.parser.ExpressionLexer
getTokenString.
getTolerance() - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbsParams
Getter for the field tolerance.
getToNode() - Method in class edu.cmu.tetrad.search.utils.R5R9Dijkstra.DijkstraEdge
Retrieves to-node represented by this DijkstraEdge.
getTotalEffect(Node, Node) - Method in class edu.cmu.tetrad.sem.SemIm
Calculates the total effect between two nodes.
getTotalEffects(Node, Node) - Method in class edu.cmu.tetrad.search.Ida
Calculates the total effects of node x on node y.
getTotalUsableCases() - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Returns the number of usable cases for the data.
getToVariables() - Method in class edu.cmu.tetrad.data.KnowledgeGroup
getToVariables.
getTp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.AdjacencyConfusion
Returns the true positive count.
getTp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
True positives.
getTp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.BidirectedConfusion
Returns the number of true positives.
getTp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.LocalGraphConfusion
Returns the true positives (TP) value of the LocalGraphConfusion object.
getTp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.OrientationConfusion
Getter for the field tp.
getTpc() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
True positives for common edges.
getTrekSource(Graph, List<Node>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
This method returns the source node of a given trek in a graph.
getTrial() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Getter for the field trial.
getTriple(Node) - Method in class edu.cmu.tetrad.search.utils.AlmostCycleRemover
Returns the set of triples for the given node.
getTriplesClassificationTypes() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getTriplesClassificationTypes.
getTriplesClassificationTypes() - Method in interface edu.cmu.tetrad.graph.TripleClassifier
getTriplesClassificationTypes.
getTriplesClassificationTypes() - Method in class edu.cmu.tetrad.graph.Underlines
getTriplesClassificationTypes.
getTriplesLists(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getTriplesLists.
getTriplesLists(Node) - Method in interface edu.cmu.tetrad.graph.TripleClassifier
getTriplesLists.
getTriplesLists(Node) - Method in class edu.cmu.tetrad.graph.Underlines
getTriplesLists.
getTrueDag() - Method in class edu.cmu.tetrad.study.performance.ComparisonResult
Getter for the field trueDag.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation
Returns the true graph at the specified index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.NLSemSimulation
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Returns the true graph at the specified index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
Returns the true graph at the given index.
getTrueGraph(int) - Method in interface edu.cmu.tetrad.algcomparison.simulation.Simulation
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.SingleDatasetSimulation
Gets the true graph for the simulation at the specified index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs
Returns the true graph at the given index.
getTrueGraph(int) - Method in class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
Returns the true graph at the given index.
getTrueInputs() - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Getter for the field trueInputs.
getTruePag() - Method in class edu.cmu.tetrad.search.utils.TsDagToPag
Getter for the field truePag.
getTrueTotalEffect(OrderedPair<Node>) - Method in class edu.cmu.tetrad.search.IdaCheck
Calculates the true total effect between two nodes in the graph.
getTruncLL() - Method in class edu.cmu.tetrad.sem.SemIm
The negative of the log likelihood function for the getModel model, with the constant chopped off.
getTValue(Parameter, int) - Method in interface edu.cmu.tetrad.sem.ISemIm
getTValue.
getTValue(Parameter, int) - Method in class edu.cmu.tetrad.sem.SemIm
getTValue.
getTwoCycleErrors(Graph, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns the TwoCycleErrors object that represents errors for direct feedback loops.
getTwoCycleFn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
False negatives for two-cycles.
getTwoCycleFn() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.TailConfusion
getTwoCycleFn.
getTwoCycleFp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
False positives for two-cycles.
getTwoCycleFp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.TailConfusion
getTwoCycleFp.
getTwoCycleTp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
Two positives for two-cycles.
getTwoCycleTp() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.TailConfusion
getTwoCycleTp.
getType() - Method in class edu.cmu.tetrad.data.KnowledgeGroup
Getter for the field type.
getType() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move
getType.
getType() - Method in class edu.cmu.tetrad.sem.ParamConstraint
Getter for the field type.
getType() - Method in class edu.cmu.tetrad.sem.Parameter
Getter for the field type.
getUncorrelatedShocks(int) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
getUncorrelatedShocks.
getUnderlinedTriplesFromGraph(Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Retrieves the underlined triples from the given graph that involve the specified node.
getUnderLines() - Method in class edu.cmu.tetrad.graph.Dag
Retrieves the set of underlined triples.
getUnderLines() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
getUnderLines.
getUnderLines() - Method in interface edu.cmu.tetrad.graph.Graph
getUnderLines.
getUnderLines() - Method in class edu.cmu.tetrad.graph.LagGraph
getUnderLines.
getUnderLines() - Method in class edu.cmu.tetrad.graph.SemGraph
getUnderLines.
getUnderLines() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns a set of Triple objects representing the underlines.
getUnderLines() - Method in class edu.cmu.tetrad.graph.Underlines
getUnderLines.
getUnparsedExpression() - Method in class edu.cmu.tetrad.calculator.expression.Equation
Getter for the field unparsedExpression.
getUnshieldedColliders() - Method in class edu.cmu.tetrad.search.Pcd
Retrieves the set of unshielded colliders in the graph returned by the method search().
getUnshieldedColliders() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Getter for the field unshieldedColliders.
getUnshieldedNoncolliders() - Method in class edu.cmu.tetrad.search.Pcd
Retrieves the set of unshielded noncolliders in the graph returned by the method search().
getUnshieldedNoncolliders() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Getter for the field unshieldedNoncolliders.
getUnstableBHats() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingD
Retrieves the list of unstable B matrices generated by the algorithm.
getUnstableGraphs() - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingD
Retrieves the list of unstable graphs generated by the algorithm.
getUpdatedBayesIm() - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
getUpdatedBayesIm.
getUpdatedBayesIm() - Method in class edu.cmu.tetrad.bayes.CptInvariantMarginalCalculator
Getter for the field updatedBayesIm.
getUpdatedBayesIm() - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
Getter for the field updatedBayesIm.
getUpdatedBayesIm() - Method in class edu.cmu.tetrad.bayes.Identifiability
The updated BayesIm.
getUpdatedBayesIm() - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Returns the updated Bayes IM.
getUpdatedBayesIm() - Method in interface edu.cmu.tetrad.bayes.ManipulatingBayesUpdater
Returns the updated Bayes IM.
getUpdatedBayesIm() - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
The updated BayesIm.
getUpdatedSemIm() - Method in class edu.cmu.tetrad.sem.SemUpdater
See http://en.wikipedia.org/wiki/Multivariate_normal_distribution.
getUpdateFunction() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Returns the update function.
getUpperBoundDouble() - Method in class edu.cmu.tetrad.util.ParamDescription
Getter for the field upperBoundDouble.
getUpperBoundInt() - Method in class edu.cmu.tetrad.util.ParamDescription
Getter for the field upperBoundInt.
getUpperBoundLong() - Method in class edu.cmu.tetrad.util.ParamDescription
Getter for the field upperBoundLong.
getV() - Method in class edu.cmu.tetrad.search.utils.DiscriminatingPath
Returns the node B in the discriminating path.
getV() - Method in class edu.pitt.csb.mgm.EigenDecomposition
Gets the matrix V of the decomposition.
getValidOrder(List<Node>, boolean) - Method in class edu.cmu.tetrad.graph.Paths
Returns a valid causal order for either a DAG or a CPDAG.
getValue() - Method in class edu.cmu.tetrad.sem.Mapping
getValue.
getValue() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Getter for the field value.
getValue() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbComponent
Returns the parents of this component.
getValue(int) - Method in class edu.cmu.tetrad.sem.SemProposition
Retrieves the value at the specified index.
getValue(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
Returns the boolean value in a given row of the table.
getValue(int) - Method in class edu.cmu.tetrad.util.Point
getValue.
getValue(int[]) - Method in interface edu.cmu.tetrad.data.CellTable
Returns the value of the cell specified by the given coordinates.
getValue(int[]) - Method in class edu.cmu.tetrad.data.CellTableAdTree
Returns the value of the cell specified by the given coordinates.
getValue(int[]) - Method in class edu.cmu.tetrad.data.CellTableCountSample
Returns the value of the cell specified by the given coordinates.
getValue(int[]) - Method in class edu.cmu.tetrad.util.MultiDimIntTable
Returns the value of the cell at the given coordinates.
getValue(int, double[][]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Returns the value of the function.
getValue(int, double[][]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Returns the value of the function.
getValue(int, double[][]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialFunction
Returns the value of the function.
getValue(int, double[][]) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.UpdateFunction
Returns the value of the glass function for a given factor.
getValue(int, int) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Retrieves the value from the covariance matrix at the specified row and column indices.
getValue(int, int) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Retrieves the value from the covariance matrix at the specified row and column indices.
getValue(int, int) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Retrieves the value from the covariance matrix at the specified row and column indices.
getValue(int, int) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Retrieves the value from the covariance matrix at the specified row and column indices.
getValue(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrix
Returns element (r,c)
getValue(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrixF
Returns element (r,c)
getValue(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.Matrix
Returns the value stored at element (r,c)
getValue(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.MatrixF
Returns the value stored at element (r,c)
getValue(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrix
Returns element (r,c)
getValue(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrixF
Returns element (r,c)
getValue(int, int) - Method in class edu.cmu.tetrad.util.IndexedMatrix
getValue.
getValue(int, int, int[]) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
getValue.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFn
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFp
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFpr
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyPrecision
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyRecall
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTn
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTp
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTpr
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorF1
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorPrecision
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestorRecall
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestralPrecision
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AncestralRecall
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFn
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFp
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFpr
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecision
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecisionCommonEdges
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecall
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecallCommonEdges
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTn
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTp
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeTrue
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicDiff
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicDiffPerRecord
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicTrue
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedFP
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedLatentPrecision
Calculates the percentage of correctly identified bidirected edges in an estimated graph for which a latent confounder exists in the true graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedPrecision
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedRecall
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedTP
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.BidirectedTrue
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalseNegativeBidirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalsePositiveBidirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorTruePositiveBidirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.CommonMeasuredAncestorRecallBidirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.CorrectSkeleton
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathPrecision
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathRecall
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.DensityEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.DensityTrue
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ElapsedCpuTime
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.F1Adj
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.F1All
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.F1Arrow
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.FalseNegativesAdjacencies
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.FalsePositiveAdjacencies
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.FBetaAdj
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderAlternative
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderNull
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.GraphExactlyRight
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaAverageSquaredDistance
Calculates the value of the IDA Average Squared Distance statistic.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMaxSquaredDiffEstTrue
Calculates the average maximum squared difference between the estimated and true values for a given data model and graphs.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMinSquaredDiffEstTrue
Calculates the average minimum squared difference between the estimated and true values for a given data model and graphs.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgSquaredDifference
Retrieves the value of the statistic, which is the average squared difference between the estimated and true values for a given data model and graphs.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaMaximumSquaredDifference
Calculates the value of the statistic "IDA Average Maximum Squared Difference".
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.IdaMinimumSquaredDifference
Calculates the value of the statistic "IDA Average Minimum Squared Difference".
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst2
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliedOrientationRatioEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ImpliesLegalMag
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.KnowledgeSatisfied
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalseNegativeBidirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalsePositiveBidirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorRecallBidirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorTruePositiveBidirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.LegalPag
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.LocalGraphPrecision
This method calculates the Local Graph Precision.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.LocalGraphRecall
 
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MagCgScore
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MagDgScore
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MagSemScore
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPasses
Calculates the Anderson Darling p-value > 0.05.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPassesBestOf10
Calculates the Anderson Darling p-value > 0.05.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingP
Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingPBestOf10
Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialP
Calculates the Binomial P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialPBestOf10
Calculates the Binomial P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffP
Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffPBestOf10
Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPasses
Calculates whether Kolmogorov-Smirnoff P > 0.05.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPassesBestOf10
Calculates whether Kolmogorov-Smirnoff P > 0.05.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrAdj
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrArrow
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.Maximal
Checks whether a PAG is maximal.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.MaximalityCondition
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NoAlmostCyclicPathsCondition
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NoCyclicPathsCondition
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesPrecision
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesRecall
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NonancestorPrecision
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NonancestorRecall
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedF1
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedPrecision
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedRecall
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumAmbiguousTriples
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsNotInUnshieldedCollidersEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberCollidersEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInCollidersEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInUnshieldedCollidersEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesTrue
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesTrue
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberTailsEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumberUnshieldedCollidersEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedBothNonancestorAncestor
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesTrue
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredDD
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredNL
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredPD
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumColoredPL
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCommonMeasuredAncestorBidirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDefiniteDirectedEdgeAncestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeConfounded
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeNonAncestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleEdges
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeAncestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeNonAncestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleVisibleNonancestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectBidirected
Returns the number of bidirected edges for which a latent confounder exists.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectDDAncestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectPDAncestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCorrectVisibleEdges
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumCoveringAdjacenciesInPag
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyDirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyNotDirectedPaths
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeAncestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeBnaMeasuredCounfounded
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNoMeasureAncestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNotAncNotRev
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeReversed
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdges
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsTrue
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumDirectedShouldBePartiallyDirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumEdgeInEstInTrue
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumGenuineAdjacenciesInPag
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectDDAncestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectPDAncestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectVisibleAncestors
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumLatentCommonAncestorBidirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumNondirectedEdges
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumParametersEst
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumPartiallyOrientedEdges
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumPossiblyDirected
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumUndirectedEdges
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdgeEst
Returns the number of X-->Y edges that are visible in the estimated PAG.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdges
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdgeTrue
Retrieves the number of X-->Y edges for which X-->Y is visible in the true PAG.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.OrientationPrecision
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.OrientationRecall
Calculates the Orientation Recall statistic, which measures the accuracy of the estimated orientation of edges in a graph compared to the true graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyPrecision
Calculates the adjacency precision of the estimated graph compared to the true graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyRecall
Calculates the adjacency recall compared to the true PAG (Partial Ancestral Graph).
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ParameterColumn
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.PercentAmbiguous
Calculates the percentage of ambiguous triples in the estimated graph compared to the true graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.PercentBidirectedEdges
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedEst
Calculates the proportion of semi(X, Y) in the estimated graph for which there is no semi(Y, X) in the true graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedTrue
Calculates the proportion of semi(X, Y) paths in the true graph for which there is no semi(Y, Z) path in the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.PvalueDistanceToAlpha
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.PvalueUniformityUnderNull
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPathF1
Calculates the F1 statistic for adjacencies.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPrecision
Calculates the semi-directed precision value.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.SemidirectedRecall
Calculates the Semidirected-Rec statistic, which is the proportion of (X, Y) where if there is a semidirected path in the true graph, then there is also a semidirected path in the estimated graph.
getValue(Graph, Graph, DataModel) - Method in interface edu.cmu.tetrad.algcomparison.statistic.Statistic
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.StructuralHammingDistance
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TailPrecision
Calculates the tail precision, which is the ratio of true positive arrows to the sum of true positive arrows and false positive arrows.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TailRecall
Calculates the tail recall value for a given true graph, estimated graph, and data model.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesArrows
Calculates the number of false negatives for arrows compared to the true DAG.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesTails
Calculates the number of false negatives for tails compared to the true DAG.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveArrow
Calculates the false positives for arrows compared to the true DAG.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveTails
Calculates the number of false positives for tails in the estimated graph compared to the true DAG.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionArrow
Calculates the proportion of X*->Y in the estimated graph for which there is no path Y~~>X in the true graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionTails
Calculates the proportion of X-->Y edges in the estimated graph for which there is a path X~~>Y in the true graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallArrows
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallTails
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveArrow
Calculates the number of true positives for arrows compared to the true DAG.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveDirectedPathNonancestor
Calculates the true positives for arrows compared to the true DAG.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveTails
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalseNegative
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalsePositive
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCyclePrecision
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleRecall
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Graph, Graph, DataModel) - Method in class edu.cmu.tetrad.algcomparison.statistic.TwoCycleTruePositive
Returns the value of this statistic, given the true graph and the estimated graph.
getValue(Node) - Method in class edu.cmu.tetrad.sem.SemProposition
Retrieves the value associated with the given node.
getValue(String) - Method in interface edu.cmu.tetrad.calculator.expression.Context
getValue.
getValue(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemEstimator.MyContext
Get the value of a variable or parameter.
getValue(String) - Method in class edu.cmu.tetrad.util.TetradProperties
getValue.
getValues(String) - Method in class edu.cmu.tetrad.util.Parameters
Returns the values set for the given parameter.
getVariable() - Method in class edu.cmu.tetrad.calculator.expression.Equation
Getter for the field variable.
getVariable() - Method in class edu.cmu.tetrad.calculator.expression.VariableExpression
Getter for the field variable.
getVariable() - Method in class edu.cmu.tetrad.data.Discretizer.Discretization
Retrieves the variable associated with the object.
getVariable(int) - Method in class edu.cmu.tetrad.data.BoxDataSet
getVariable.
getVariable(int) - Method in interface edu.cmu.tetrad.data.DataSet
getVariable.
getVariable(int) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getVariable.
getVariable(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialTerm
Returns the index'th variable.
getVariable(Node) - Method in class edu.cmu.tetrad.bayes.BayesPm
Returns the variable for the given node.
getVariable(Node) - Method in class edu.cmu.tetrad.search.IndTestIod
Returns the variable associated with the given node in the graph.
getVariable(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
getVariable.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.BasisFunctionBicScore
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.BdeuScore
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.ConditionalGaussianBicScore
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.DegenerateGaussianBicScore
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.DiscreteBicScore
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.EbicScore
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.FisherZScore
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.GicScores
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.MagDgBicScore
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.MSeparationScore
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.MVPBicScore
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.PoissonPriorScore
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.PositiveCorrScore
Returns the variable with the given name.
getVariable(String) - Method in interface edu.cmu.tetrad.algcomparison.score.ScoreWrapper
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.SemBicScore
Retrieves the variable with the given name from the data set.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.SemBicScoreDeterministic
Retrieves the Node with the given name from the data set.
getVariable(String) - Method in class edu.cmu.tetrad.algcomparison.score.ZhangShenBoundScore
Retrieves the variable with the given name from the data set.
getVariable(String) - Method in class edu.cmu.tetrad.bayes.BayesProperties
Returns the variable with the given name (assumed the target).
getVariable(String) - Method in class edu.cmu.tetrad.bayes.Evidence
getVariable.
getVariable(String) - Method in class edu.cmu.tetrad.data.BoxDataSet
getVariable.
getVariable(String) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Retrieves a Node instance from the covariance matrix corresponding to the specified variable name.
getVariable(String) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Retrieves a Node instance from the covariance matrix corresponding to the specified variable name.
getVariable(String) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Retrieves a Node instance from the covariance matrix corresponding to the specified variable name.
getVariable(String) - Method in interface edu.cmu.tetrad.data.DataModel
getVariable.
getVariable(String) - Method in class edu.cmu.tetrad.data.DataModelList
getVariable.
getVariable(String) - Method in interface edu.cmu.tetrad.data.DataSet
getVariable.
getVariable(String) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Retrieves a Node instance from the covariance matrix corresponding to the specified variable name.
getVariable(String) - Method in class edu.cmu.tetrad.data.IndependenceFacts
getVariable.
getVariable(String) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getVariable.
getVariable(String) - Method in class edu.cmu.tetrad.data.TimeSeriesData
getVariable.
getVariable(String) - Method in interface edu.cmu.tetrad.search.IndependenceTest
Returns The variable by the given name.
getVariable(String) - Method in class edu.cmu.tetrad.search.IndTestIod
Retrieves a variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the variable with the given name.
getVariable(String) - Method in interface edu.cmu.tetrad.search.score.Score
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Returns the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
Retrieves a variable node based on its name.
getVariable(String) - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Retrieves the Node object that matches the given name from the list of nodes.
getVariable(String) - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Gets the variable with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.search.test.Kci
Returns the variable of the given name.
getVariable(String) - Method in class edu.cmu.tetrad.search.test.MsepTest
Returns the Node object with the given name.
getVariable(String) - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Retrieves the Node object with the specified name.
getVariable(String) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Returns The variable by the given name.
getVariable(String) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Retrieves the node associated with the given variable name.
getVariable(String) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
Retrieves the variable with the specified name.
getVariable(String) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Retrieves a Node from the variables list that matches the specified target name.
getVariable(String) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Retrieves a Node from the variables list that matches the specified target name.
getVariable(String) - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Retrieves a variable node by its target name.
getVariable(String) - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
Returns The variable by the given name.
getVariableMeans() - Method in class edu.cmu.tetrad.sem.SemIm
Getter for the field variableMeans.
getVariableName(int) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Retrieves the name of the variable at the specified index from the covariance matrix.
getVariableName(int) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Retrieves the name of the variable at the specified index from the covariance matrix.
getVariableName(int) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Retrieves the name of the variable at the specified index from the covariance matrix.
getVariableName(int) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Retrieves the name of the variable at the specified index from the covariance matrix.
getVariableNames() - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the list of variable names.
getVariableNames() - Method in class edu.cmu.tetrad.bayes.BayesPm
Returns the variable names.
getVariableNames() - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
getVariableNames.
getVariableNames() - Method in class edu.cmu.tetrad.bayes.MlBayesIm
getVariableNames.
getVariableNames() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
getVariableNames.
getVariableNames() - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
getVariableNames.
getVariableNames() - Method in class edu.cmu.tetrad.data.BoxDataSet
getVariableNames.
getVariableNames() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
getVariableNames.
getVariableNames() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
getVariableNames.
getVariableNames() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
getVariableNames.
getVariableNames() - Method in class edu.cmu.tetrad.data.DataModelList
getVariableNames.
getVariableNames() - Method in interface edu.cmu.tetrad.data.DataSet
getVariableNames.
getVariableNames() - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Retrieves the list of names of the variables in the covariance matrix.
getVariableNames() - Method in class edu.cmu.tetrad.data.IndependenceFacts
getVariableNames.
getVariableNames() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
getVariableNames.
getVariableNames() - Method in class edu.cmu.tetrad.data.TimeSeriesData
getVariableNames.
getVariableNames() - Method in interface edu.cmu.tetrad.data.VariableSource
Returns the variable names associated with this getVariableNames.
getVariableNames() - Method in interface edu.cmu.tetrad.search.IndependenceTest
Returns the list of names for the variables in getNodesInEvidence.
getVariableNode(String) - Method in class edu.cmu.tetrad.sem.SemIm
getVariableNode.
getVariableNodes() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Returns the list of variable nodes--that is, node that is not error nodes.
getVariableNodes() - Method in interface edu.cmu.tetrad.sem.ISemIm
getVariableNodes.
getVariableNodes() - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Getter for the field variableNodes.
getVariableNodes() - Method in class edu.cmu.tetrad.sem.SemIm
The list of measured and latent nodes for the semPm.
getVariableNodes() - Method in class edu.cmu.tetrad.sem.SemPm
Getter for the field variableNodes.
getVariableNodes() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
getVariableNodes.
getVariables() - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns the list of variables.
getVariables() - Method in class edu.cmu.tetrad.bayes.BayesImProbs
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.bayes.BayesPm
getVariables.
getVariables() - Method in class edu.cmu.tetrad.bayes.CellTableProbs
getVariables.
getVariables() - Method in class edu.cmu.tetrad.bayes.DataSetProbs
getVariables.
getVariables() - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
getVariables.
getVariables() - Method in class edu.cmu.tetrad.bayes.DirichletDataSetProbs
getVariables.
getVariables() - Method in class edu.cmu.tetrad.bayes.IntAveDataSetProbs
getVariables.
getVariables() - Method in class edu.cmu.tetrad.bayes.MlBayesIm
getVariables.
getVariables() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
getVariables.
getVariables() - Method in class edu.cmu.tetrad.bayes.StoredCellProbs
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
getVariables.
getVariables() - Method in class edu.cmu.tetrad.data.BoxDataSet
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.data.DataModelList
getVariables.
getVariables() - Method in interface edu.cmu.tetrad.data.DataSet
getVariables.
getVariables() - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Retrieves the list of Node variables for the covariance matrix.
getVariables() - Method in class edu.cmu.tetrad.data.IndependenceFacts
getVariables.
getVariables() - Method in class edu.cmu.tetrad.data.Knowledge
Get a list of variables.
getVariables() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.data.TimeSeriesData
getVariables.
getVariables() - Method in interface edu.cmu.tetrad.data.VariableSource
Returns the list of variables associated with this object.
getVariables() - Method in class edu.cmu.tetrad.search.Boss
Returns the variables.
getVariables() - Method in class edu.cmu.tetrad.search.CompositeIndependenceTest
getVariables.
getVariables() - Method in class edu.cmu.tetrad.search.Grasp
Returns the variables.
getVariables() - Method in interface edu.cmu.tetrad.search.IndependenceTest
getVariables.
getVariables() - Method in class edu.cmu.tetrad.search.IndTestIod
Returns the list of TetradNodes over which this independence checker is capable of determining independence relations-- that is, all the variables in the given graph or the given data set.
getVariables() - Method in class edu.cmu.tetrad.search.PermutationSearch
Retrieves the list of variables.
getVariables() - Method in class edu.cmu.tetrad.search.score.BasisFunctionBicScore
Retrieves the list of nodes representing the variables in the basis function score.
getVariables() - Method in class edu.cmu.tetrad.search.score.BdeScore
Returns the variables present in the DataSet associated with this method.
getVariables() - Method in class edu.cmu.tetrad.search.score.BdeuScore
Retrieves the list of variables used in the object.
getVariables() - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.score.DegenerateGaussianScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.score.EbicScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.score.GicScores
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.score.GraphScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.score.ImagesScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.score.IndTestScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.score.MvpScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.score.PoissonPriorScore
The variables of the score.
getVariables() - Method in interface edu.cmu.tetrad.search.score.Score
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the variables of the covariance matrix.
getVariables() - Method in class edu.cmu.tetrad.search.score.ZsbScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.Sp
Returns the list of variables associated with this object.
getVariables() - Method in interface edu.cmu.tetrad.search.SuborderSearch
The list of all variables, in order.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Returns the list of variables over which this independence checker is capable of determining independence relations-- that is, all the variables in the given graph or the given data set.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalCorrelation
Returns the list of variables over which this independence checker is capable of determining independence relations-- that is, all the variables in the given graph or the given data set.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Returns the list of variables over which this independence checker is capable of determining independence relations.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Returns the list of searchVariables over which this independence checker is capable of determinining independence relations.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Returns the list of variables over which this independence checker is capable of determinine independence relations-- that is, all the variables in the given graph or the given data set.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
Returns the list of variables used in this method.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Returns the list of variables over which this independence checker is capable of determinine independence relations-- that is, all the variables in the given graph or the given data set.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Return the list of variables over which this independence checker is capable of determining independence relations-- that is, all the variables in the given graph or the given data set.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Returns the list of variables over which this independence checker is capable of determinine independence relations-- that is, all the variables in the given graph or the given data set.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
Returns the list of variables for the facts.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestMulti
Retrieves the list of variables associated with this object.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestMvpLrt
Returns the list of searchVariables over which this independence checker is capable of determinining independence relations.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Returns the list of variables used in this object.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestRegression
Returns the list of variables associated with this object.
getVariables() - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Returns the list of variables over which this independence checker is capable of determinine independence relations-- that is, all the variables in the given graph or the given data set.
getVariables() - Method in class edu.cmu.tetrad.search.test.Kci
Returns the list of variables over which this independence checker is capable of determinining independence relations.
getVariables() - Method in class edu.cmu.tetrad.search.test.MsepTest
Return the list of TetradNodes over which this independence checker is capable of determinine independence relations-- that is, all the variables in the given graph or the given data set.
getVariables() - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Returns the list of variables over which this independence checker is capable of determinining independence relations.
getVariables() - Method in class edu.cmu.tetrad.search.utils.Bes
Returns the variables being searched over.
getVariables() - Method in class edu.cmu.tetrad.search.utils.BesPermutation
Returns the variables.
getVariables() - Method in class edu.cmu.tetrad.search.utils.DagSepsets
Retrieves the list of variables.
getVariables() - Method in class edu.cmu.tetrad.search.utils.DeltaSextadTest
Returns the variables of the data being used.
getVariables() - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
getVariables.
getVariables() - Method in interface edu.cmu.tetrad.search.utils.SepsetProducer
Retrieves the list of variables.
getVariables() - Method in class edu.cmu.tetrad.search.utils.SepsetsGreedy
Retrieves the variables used in the independence test.
getVariables() - Method in class edu.cmu.tetrad.search.utils.SepsetsMaxP
Retrieves the variables used in the independence test.
getVariables() - Method in class edu.cmu.tetrad.search.utils.SepsetsMinP
Retrieves the variables used in the independence test.
getVariables() - Method in class edu.cmu.tetrad.search.utils.SepsetsPossibleMsep
Retrieves the list of variables.
getVariables() - Method in class edu.cmu.tetrad.search.utils.SepsetsSet
Retrieves the list of variables.
getVariables() - Method in interface edu.cmu.tetrad.search.utils.TetradTest
getVariables.
getVariables() - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
getVariables.
getVariables() - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
getVariables.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Retrieves the list of variables used in the independence test.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Getter for the field variables.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
Retrieves the list of variables used in the original data set.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMnlrLr
getVariables.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
getVariables.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Retrieves the list of variables used in the independence test.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
getVariables.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Retrieves the list of variables associated with this instance.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Retrieves the list of variables associated with this ISBicScore instance.
getVariables() - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Retrieves a list of variables represented as nodes.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.MnlrScore
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
getVariables.
getVariables() - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
The variables of the score.
getVariables() - Method in class edu.cmu.tetrad.sem.DagScorer
Getter for the field variables.
getVariables() - Method in interface edu.cmu.tetrad.sem.Scorer
getVariables.
getVariables() - Method in class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
getVariables.
getVariables(List<Node>, List<Node>, List<Node>) - Method in class edu.cmu.tetrad.search.MarkovCheck
Returns the variables of the independence test.
getVariablesInEvidence() - Method in class edu.cmu.tetrad.bayes.Evidence
getVariablesInEvidence.
getVariablesNotInTiers() - Method in class edu.cmu.tetrad.data.Knowledge
getVariablesNotInTiers.
getVariableSource() - Method in class edu.cmu.tetrad.bayes.Evidence
getVariableSource.
getVariableSource() - Method in class edu.cmu.tetrad.bayes.Proposition
Getter for the field variableSource.
getVariablesTemplate() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Retrieves the variable template.
getVariableValues(int) - Method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
getVariableValues.
getVariableVectors() - Method in class edu.cmu.tetrad.data.VerticalDoubleDataBox
getVariableVectors.
getVariableVectors() - Method in class edu.cmu.tetrad.data.VerticalIntDataBox
getVariableVectors.
getVariance(Node, Matrix) - Method in interface edu.cmu.tetrad.sem.ISemIm
getVariance.
getVariance(Node, Matrix) - Method in class edu.cmu.tetrad.sem.SemIm
Returns the variance for a given node.
getVarianceParameter(Node) - Method in class edu.cmu.tetrad.sem.SemPm
Return the parameter for the variance of the error term for the given node, which is the variance of the node if the node is an error term, and the variance of the node's error term if not.
getVariances() - Method in class edu.cmu.tetrad.search.work_in_progress.MixtureModel
getVariances.
getVarNames() - Method in interface edu.cmu.tetrad.search.utils.TetradTest
getVarNames.
getVarNames() - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
getVarNames.
getVarNames() - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
getVarNames.
getVarNames() - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
getVarNames.
getVarNode(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
getVarNode.
getVarRy(int, int[], Matrix, ICovarianceMatrix, boolean, boolean) - Static method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the variance of the residual of the regression of the ith variable on its parents.
getVarsNotInCluster(List<String>) - Method in class edu.cmu.tetrad.data.Clusters
getVarsNotInCluster.
getVarsPerInd() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Getter for the field varsPerInd.
getVarsPerInd() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraphParams
Returns the number of variables per individual.
getVector() - Method in class edu.cmu.tetrad.util.Point
Getter for the field vector.
getVicinity(Edge, int) - Method in class edu.cmu.tetrad.simulation.Vicinity
getVicinity.
getVT() - Method in class edu.pitt.csb.mgm.EigenDecomposition
Gets the transpose of the matrix V of the decomposition.
getW() - Method in class edu.cmu.tetrad.search.FastIca.IcaResult
Returns the estimated un-mixing matrix.
getW() - Method in class edu.cmu.tetrad.search.utils.DiscriminatingPath
Retrieves the node A in the discriminating path.
getWeight() - Method in class edu.cmu.tetrad.search.FciOrientDijkstra.DijkstraEdge
Returns the weight of the edge.
getWeight() - Method in class edu.cmu.tetrad.search.utils.R5R9Dijkstra.DijkstraEdge
Retrieves the weight of the edge represented by this DijkstraEdge.
getWeight(Statistic) - Method in class edu.cmu.tetrad.algcomparison.statistic.Statistics
The utility weight for the statistic.
getWeights() - Method in class edu.cmu.tetrad.search.work_in_progress.MixtureModel
getWeights.
getWrappedScore() - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Returns the score object that this test wraps.
getWThreshold() - Method in class edu.cmu.tetrad.search.Dagma
Retrieves the value of the wThreshold field.
getWwi() - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso.Result
Getter for the field wwi.
getX() - Method in class edu.cmu.tetrad.graph.IndependenceFact
Getter for the field x.
getX() - Method in class edu.cmu.tetrad.graph.Triple
Getter for the field x.
getX() - Method in class edu.cmu.tetrad.search.FastIca.IcaResult
Returns the pre-processed data matrix.
getX() - Method in class edu.cmu.tetrad.search.utils.DiscriminatingPath
Returns the node E in the discriminating path.
getX() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms.GraphoidIndFact
Returns the set of nodes X.
getX() - Method in class edu.cmu.tetrad.util.PointXy
Getter for the field x.
getxMeans() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
THe array of means.
getXSquare() - Method in class edu.cmu.tetrad.search.test.ChiSquareTest.Result
Returns the chi square value, or NaN if the chi square value cannot be determined.
getxStdDevs() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
The array of standard devs.
gety() - Method in class edu.cmu.tetrad.search.FciOrientDijkstra.DijkstraEdge
Returns the node.
getY() - Method in class edu.cmu.tetrad.graph.IndependenceFact
Getter for the field y.
getY() - Method in class edu.cmu.tetrad.graph.Triple
Getter for the field y.
getY() - Method in class edu.cmu.tetrad.search.utils.DiscriminatingPath
Returns the node C in the discriminating path.
getY() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms.GraphoidIndFact
Returns the set of nodes Y.
getY() - Method in class edu.cmu.tetrad.util.PointXy
Getter for the field y.
getZ() - Method in class edu.cmu.tetrad.graph.IndependenceFact
getZ.
getZ() - Method in class edu.cmu.tetrad.graph.Triple
Getter for the field z.
getZ() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms.GraphoidIndFact
Returns the set of nodes Z.
getZForAlpha(double) - Static method in class edu.cmu.tetrad.util.StatUtils
getZForAlpha.
Gfci - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
The Gfci class represents the Greedy Fast Causal Inference algorithm.
Gfci() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
The Gfci class represents the Greedy Fast Causal Inference algorithm.
Gfci(IndependenceWrapper, ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Constructs a new instance of Gfci with the given IndependenceWrapper and ScoreWrapper.
GFci - Class in edu.cmu.tetrad.search
Implements a modification of FCI that started by running the FGES algorithm and then fixes that result to be correct for latent variables models.
GFci(IndependenceTest, Score) - Constructor for class edu.cmu.tetrad.search.GFci
Constructs a new GFci algorithm with the given independence test and score.
GFCI - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.Algorithm
Constant for the GFCI algorithm.
gfciExtraEdgeRemovalStep(Graph, Graph, List<Node>, SepsetProducer, int, boolean) - Static method in class edu.cmu.tetrad.graph.GraphUtils
The extra-edge removal step for GFCI.
gfciR0(Graph, Graph, SepsetProducer, Knowledge, boolean, Set<Triple>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Applies the GFCI-R0 algorithm to orient edges in a pag based on a reference CPDAG, sepsets, and knowledge.
GIC2 - Enum constant in enum class edu.cmu.tetrad.search.score.GicScores.RuleType
The GIC2 rule.
GIC5 - Enum constant in enum class edu.cmu.tetrad.search.score.GicScores.RuleType
The GIC5 rule.
GIC6 - Enum constant in enum class edu.cmu.tetrad.search.score.GicScores.RuleType
The GIC6 rule.
GicScores - Class in edu.cmu.tetrad.algcomparison.score
The GicScores class is an implementation of the ScoreWrapper interface that calculates the Generalized Information Criterion (GIC) scores for a given data model.
GicScores - Class in edu.cmu.tetrad.search.score
Implements scores motivated by the Generalized Information Criterion (GIC) approach as given in Kim et al.
GicScores() - Constructor for class edu.cmu.tetrad.algcomparison.score.GicScores
Constructs a new instance of the algorithm.
GicScores(DataSet, boolean) - Constructor for class edu.cmu.tetrad.search.score.GicScores
Constructs the score using a covariance matrix.
GicScores(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.search.score.GicScores
Constructs the score using a covariance matrix.
GicScores.RuleType - Enum Class in edu.cmu.tetrad.search.score
Gives the options for the rules to use for calculating the scores.
GICScoreTests - Class in edu.cmu.tetrad.algcomparison.independence
Represents a class for Generalized Information Criterion Score Tests.
GICScoreTests() - Constructor for class edu.cmu.tetrad.algcomparison.independence.GICScoreTests
Represents a class for Generalized Information Criterion Score Tests.
Glasso - Class in edu.cmu.tetrad.algcomparison.algorithm.other
GLASSO.
Glasso - Class in edu.cmu.tetrad.search.work_in_progress
A translation from Tibshirani's 2008 Fortran implementation of glasso.
Glasso() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.other.Glasso
Constructs a new instance of the algorithm.
Glasso(Matrix) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Glasso
Constructor for Glasso.
Glasso.Result - Class in edu.cmu.tetrad.search.work_in_progress
Return value of the algorithm.
GLOBAL_MARKOV - Enum constant in enum class edu.cmu.tetrad.search.ConditioningSetType
Testing all possible independence facts implied by the graph.
goToBookmark() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Retries the bookmark with key = Integer.MIN_VALUE and removes the bookmark.
goToBookmark(int) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Retrieves the bookmarked state for index 'key' and removes that bookmark.
grabLayout(List<Node>) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
grabLayout.
Graph - Enum constant in enum class edu.cmu.tetrad.data.DataType
Graph.
Graph - Interface in edu.cmu.tetrad.graph
Implements a graph capable of storing edges of type N1 *-# N2 where * and # are endpoints of type Endpoint.
Graph(Graph, boolean) - Constructor for class edu.cmu.tetrad.search.FciOrientDijkstra.Graph
Represents a graph used in Dijkstra's algorithm.
Graph(Graph, R5R9Dijkstra.Rule) - Constructor for class edu.cmu.tetrad.search.utils.R5R9Dijkstra.Graph
Represents a graph for Dijkstra's algorithm.
graphAttributesToText(Graph, String) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts the attributes of a given graph into a text format.
GraphChange - Class in edu.cmu.tetrad.search.work_in_progress
Provides s a data structure created mainly for use in the ION search algorithm.
GraphChange() - Constructor for class edu.cmu.tetrad.search.work_in_progress.GraphChange
Default constructor, holds no changes.
GraphChange(GraphChange) - Constructor for class edu.cmu.tetrad.search.work_in_progress.GraphChange
Copy constructor.
graphComparison(Graph, Graph, PrintStream) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
graphComparison.
GraphComparison(int, int, int, int, int, int, double, double, double, double, int, List<Edge>, List<Edge>, int[][]) - Constructor for class edu.cmu.tetrad.graph.GraphUtils.GraphComparison
Constructs a new GraphComparison.
graphEdgesToText(Graph, String) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts the edges of a graph to text representation.
GraphExactlyRight - Class in edu.cmu.tetrad.algcomparison.statistic
Return a 1 if the graph is exactly right, 0 otherwise.
GraphExactlyRight() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.GraphExactlyRight
Constructor for GraphExactlyRight.
graphFromMGM() - Method in class edu.pitt.csb.mgm.Mgm
Converts MGM object to Graph object with edges if edge parameters are non-zero.
GraphInitializer - Interface in edu.cmu.tetrad.study.gene.tetrad.gene.history
Instantiations of this interface know how to randomize lag graphs in particular ways.
GraphInPag - Class in edu.cmu.tetrad.search.utils
Contains methods which can be used to determine whether a directed graph is in the equivalence class determined by the given PAG.
graphInPagStep0(Graph, Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphInPag
This method implements step (1) of the definition.
graphInPagStep1(Graph, Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphInPag
graphInPagStep1.
graphInPagStep2(Graph, Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphInPag
graphInPagStep2.
graphInPagStep3(Graph, Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphInPag
graphInPagStep3.
graphInPagStep4(Graph, Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphInPag
graphInPagStep4.
graphInPagStep5(Graph, Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphInPag
graphInPagStep5.
GraphNode - Class in edu.cmu.tetrad.graph
Implements a basic node in a graph--that is, a node that is not itself a variable.
GraphNode(GraphNode) - Constructor for class edu.cmu.tetrad.graph.GraphNode
Copy constructor.
GraphNode(String) - Constructor for class edu.cmu.tetrad.graph.GraphNode
Constructs a new Tetrad node with the given (non-null) string.
graphNodeAttributesToText(Graph, String, char) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts the attributes of nodes in a graph to text format.
graphNodesToText(Graph, String, char) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts the nodes of a graph to a formatted text representation.
graphoid() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Checks whether teh IM is a semigraphoid.
GraphoidAxioms - Class in edu.cmu.tetrad.search.utils
Checks the graphoid axioms for a set of Independence Model statements.
GraphoidAxioms(Set<GraphoidAxioms.GraphoidIndFact>, List<Node>) - Constructor for class edu.cmu.tetrad.search.utils.GraphoidAxioms
Constructor.
GraphoidAxioms(Set<GraphoidAxioms.GraphoidIndFact>, List<Node>, Map<GraphoidAxioms.GraphoidIndFact, String>) - Constructor for class edu.cmu.tetrad.search.utils.GraphoidAxioms
Constructor.
GraphoidAxioms.GraphoidIndFact - Class in edu.cmu.tetrad.search.utils
Represents a graphoid independence fact--i.e., a fact in a general independence model (IM) X _||_Y | Z.
GraphoidIndFact(Set<Node>, Set<Node>, Set<Node>) - Constructor for class edu.cmu.tetrad.search.utils.GraphoidAxioms.GraphoidIndFact
Constructor.
GraphRandomizer - Interface in edu.cmu.tetrad.study.gene.tetrad.gene.history
Instantiations of this interface know how to randomize update graphs in particular ways.
graphRMatrixTxt(Graph) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
graphRMatrixTxt.
GraphSampling - Class in edu.cmu.tetrad.util
A utility for computing frequency probabilities.
GraphSaveLoadUtils - Class in edu.cmu.tetrad.graph
Methods to load or save graphs.
GraphScore - Class in edu.cmu.tetrad.search.score
Implements a pscudo-"score" that implmenets implements Chickering and Meek's (2002) locally consistent score criterion.
GraphScore(IndependenceFacts) - Constructor for class edu.cmu.tetrad.search.score.GraphScore
Constructs a GraphScore from a list of independence facts.
GraphScore(Graph) - Constructor for class edu.cmu.tetrad.search.score.GraphScore
Constructs a GraphScore from a DAG.
GraphSearchUtils - Class in edu.cmu.tetrad.search.utils
Provides some graph utilities for search algorithm.
GraphSearchUtils.CpcTripleType - Enum Class in edu.cmu.tetrad.search.utils
Gives the options for triple type for a conservative unshielded collider orientation, which may be "collider" or "noncollider" or "ambiguous".
GraphSearchUtils.LegalMagRet - Class in edu.cmu.tetrad.search.utils
Stores a result for checking whether a graph is a legal MAG--(a) whether it is (a boolean), and (b) the reason why it is not, if it is not (a String).
GraphSearchUtils.LegalPagRet - Class in edu.cmu.tetrad.search.utils
Stores a result for checking whether a graph is a legal PAG--(a) whether it is (a boolean), and (b) the reason why it is not, if it is not (a String).
graphToAmatCpag(Graph) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
Converts a given graph into an adjacency matrix in CPAG format.
graphToAmatPag(Graph) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
Saves a PAG in the "amat.pag" format of PCALG.
graphToDot(Graph) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
Converts a graph to a Graphviz .dot file
graphToDot(Graph, File) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
graphToDot.
graphToLagGraph(Graph, int) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
graphToLagGraph.
graphToLavaan(Graph) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
graphToLavaan.
graphToMatrix(Graph) - Static method in class edu.pitt.csb.mgm.MixedUtils
graphToMatrix.
graphToMatrix(Graph, double, double) - Static method in class edu.pitt.csb.mgm.MixedUtils
graphToMatrix.
GraphTools - Class in edu.cmu.tetrad.bayes
A utility class containing graph function from graph theory.
graphToPcalg(Graph) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
graphToPcalg.
graphToXml(Graph) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
graphToXml.
GraphTransforms - Class in edu.cmu.tetrad.graph
Transformations that transform one graph into another.
GraphTypes - Class in edu.cmu.tetrad.algcomparison.graph
Jun 4, 2019 3:21:47 PM
GraphUtils - Class in edu.cmu.tetrad.graph
Utility class for working with graphs.
GraphUtils.GraphComparison - Class in edu.cmu.tetrad.graph
Represents a comparison between two graphs.
GraphUtils.GraphType - Enum Class in edu.cmu.tetrad.graph
The GraphType enum represents the types of graphs that can be used in the application.
GraphUtils.TwoCycleErrors - Class in edu.cmu.tetrad.graph
Two-cycle errors.
GraphWithPValue(Graph, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.GraphWithPValue
Constructor for GraphWithPValue.
grasp(TeyssierScorer) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
grasp.
Grasp - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
GRaSP (Greedy Relaxations of Sparsest Permutation)
Grasp - Class in edu.cmu.tetrad.search
Implements the GRaSP algorithms, which uses a certain procedure to search in the space of permutations of variables for ones that imply CPDAGs that are especially close to the CPDAG of the true model.
Grasp() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Constructor for Grasp.
Grasp(IndependenceWrapper, ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Constructor for Grasp.
Grasp(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.Grasp
Constructor for a test.
Grasp(IndependenceTest, Score) - Constructor for class edu.cmu.tetrad.search.Grasp
Constructor that takes both a test and a score; only one is used-- the parameter setting will decide which.
Grasp(Score) - Constructor for class edu.cmu.tetrad.search.Grasp
Constructor for a score.
GRASP - Enum constant in enum class edu.cmu.tetrad.search.FaskOrig.AdjacencyMethod
A permutation search with the GRASP algorithm.
GRASP - Enum constant in enum class edu.cmu.tetrad.search.LvLite.START_WITH
Start with GRaSP.
GRASP_ALG - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_ALG="graspAlg"
GRASP_BREAK_AFTER_IMPROVEMENT - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_BREAK_AFTER_IMPROVEMENT="graspBreakAFterImprovement"
GRASP_CHECK_COVERING - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_CHECK_COVERING="graspCheckCovering"
GRASP_DEPTH - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_DEPTH="graspDepth"
GRASP_FORWARD_TUCK_ONLY - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_FORWARD_TUCK_ONLY="graspForwardTuckOnly"
GRASP_NONSINGULAR_DEPTH - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_NONSINGULAR_DEPTH="graspNonSingularDepth"
GRASP_ORDERED_ALG - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_ORDERED_ALG="graspOrderedAlg"
GRASP_SINGULAR_DEPTH - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_SINGULAR_DEPTH="graspSingularDepth"
GRASP_TOLERANCE_DEPTH - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_TOLERANCE_DEPTH="graspToleranceDepth"
GRASP_USE_RASKUTTI_UHLER - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_USE_RASKUTTI_UHLER="graspUseRaskuttiUhler"
GRASP_USE_SCORE - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_USE_SCORE="graspUseScore"
GRASP_USE_VP_SCORING - Static variable in class edu.cmu.tetrad.util.Params
Constant GRASP_USE_VP_SCORING="graspUseVpScoring"
GraspFci - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
Adjusts GFCI to use a permutation algorithm (such as BOSS-Tuck) to do the initial steps of finding adjacencies and unshielded colliders.
GraspFci - Class in edu.cmu.tetrad.search
Uses GRaSP in place of FGES for the initial step in the GFCI algorithm.
GraspFci() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Constructor for GraspFci.
GraspFci(IndependenceWrapper, ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Constructor for GraspFci.
GraspFci(IndependenceTest, Score) - Constructor for class edu.cmu.tetrad.search.GraspFci
Constructs a new GraspFci object.
GraspTol - Class in edu.cmu.tetrad.search.work_in_progress
Implements the GRASP algorithms, with various execution flags.
GraspTol(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.work_in_progress.GraspTol
Constructor for GraspTol.
GraspTol(IndependenceTest, Score) - Constructor for class edu.cmu.tetrad.search.work_in_progress.GraspTol
Constructor for GraspTol.
GraspTol(Score) - Constructor for class edu.cmu.tetrad.search.work_in_progress.GraspTol
Constructor for GraspTol.
GraspTol(List<Node>) - Constructor for class edu.cmu.tetrad.search.work_in_progress.GraspTol
Constructor for GraspTol.
GREEDY - Enum constant in enum class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased.BlockingType
Greedy blocking.
GrowShrink - Class in edu.cmu.tetrad.search
Implements the Grow-Shrink algorithm of Margaritis and Thrun, a simple yet correct and useful Markov blanket search.
GrowShrink(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.GrowShrink
Constructs a new search.
GrowShrinkTree - Class in edu.cmu.tetrad.search.utils
GrowShrinkTree class.
GrowShrinkTree(Score, Map<Node, Integer>, Node) - Constructor for class edu.cmu.tetrad.search.utils.GrowShrinkTree
Constructor for GrowShrinkTree.
GSquare - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Fisher Z test.
GSquare() - Constructor for class edu.cmu.tetrad.algcomparison.independence.GSquare
GSquare class represents a wrapper for the G Square test, which is a statistical test for independence between two variables conditional on a third variable.
GT - Enum constant in enum class edu.cmu.tetrad.sem.ParamConstraintType
Represents a parameter constraint type GT (greater than).
GUARANTEE_ACYCLIC - Static variable in class edu.cmu.tetrad.util.Params
Constant GUARANTEE_ACYCLIC="guaranteeAcyclic"
GUARANTEE_CPDAG - Static variable in class edu.cmu.tetrad.util.Params
Constant GUARANTEE_CPDAG="guaranteeCpdag"
GUARANTEE_IID - Static variable in class edu.cmu.tetrad.util.Params
Constant GUARANTEE_IID="guaranteeIid"
GUARANTEE_PAG - Static variable in class edu.cmu.tetrad.util.Params
Constant GUARANTEE_PAG="guaranteePag"
guaranteePag(Graph, FciOrient, Knowledge, Set<Triple>, Set<Triple>, boolean, Set<Node>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Guarantees a legal PAG by repairing deviations of a graph from a legal PAG (partial ancestral graph).

H

handlesUnmeasuredConfounder(Class) - Method in class edu.cmu.tetrad.annotation.AlgorithmAnnotations
Checks if the algorithm handles unmeasured confounders.
HandleyConvert - Class in edu.cmu.tetrad.study.gene.tetrad.gene.util
The purpose of this little converter is to convert "effect" files into "cause" (BasicLagGraph) files.
hasComplexEigenvalues() - Method in class edu.pitt.csb.mgm.EigenDecomposition
Returns whether the calculated eigen values are complex or real.
hasDimensions(double[][], int, int) - Static method in class edu.cmu.tetrad.util.MatrixUtils
hasDimensions.
hashCode() - Method in class edu.cmu.tetrad.annotation.AnnotatedClass
 
hashCode() - Method in class edu.cmu.tetrad.bayes.Evidence
hashCode.
hashCode() - Method in class edu.cmu.tetrad.bayes.Manipulation
hashCode.
hashCode() - Method in class edu.cmu.tetrad.bayes.Proposition
hashCode.
hashCode() - Method in class edu.cmu.tetrad.data.Clusters
Computes a hashcode.
hashCode() - Method in class edu.cmu.tetrad.data.ContinuousVariable
hashCode.
hashCode() - Method in class edu.cmu.tetrad.data.DataModelList
hashCode.
hashCode() - Method in class edu.cmu.tetrad.data.DiscreteVariable
hashCode.
hashCode() - Method in class edu.cmu.tetrad.data.Knowledge
Computes a hashcode.
hashCode() - Method in class edu.cmu.tetrad.data.KnowledgeEdge
hashCode.
hashCode() - Method in class edu.cmu.tetrad.data.KnowledgeGroup
Computes a hashcode.
hashCode() - Method in class edu.cmu.tetrad.graph.Edge
hashCode.
hashCode() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
hashCode() - Method in class edu.cmu.tetrad.graph.GraphNode
hashCode.
hashCode() - Method in class edu.cmu.tetrad.graph.IndependenceFact
hashCode.
hashCode() - Method in interface edu.cmu.tetrad.graph.Node
Removes a property change listener.
hashCode() - Method in class edu.cmu.tetrad.graph.NodePair
hashCode.
hashCode() - Method in class edu.cmu.tetrad.graph.OrderedPair
hashCode.
hashCode() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns the hash code value for this object.
hashCode() - Method in class edu.cmu.tetrad.graph.Triple
hashCode.
hashCode() - Method in record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Returns a hash code value for this object.
hashCode() - Method in class edu.cmu.tetrad.search.score.ScoredGraph
Return s the hashcode of the score.
hashCode() - Method in record class edu.cmu.tetrad.search.score.SemBicScore.CovAndCoefs
Returns a hash code value for this object.
hashCode() - Method in record class edu.cmu.tetrad.search.test.Kci.EigenReturn
Returns a hash code value for this object.
hashCode() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms.GraphoidIndFact
Returns the hash code.
hashCode() - Method in class edu.cmu.tetrad.search.utils.Sextad
hashCode.
hashCode() - Method in class edu.cmu.tetrad.search.utils.Tetrad
hashCode.
hashCode() - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
hashCode.
hashCode() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.GraphWithPValue
hashCode.
hashCode() - Method in class edu.cmu.tetrad.search.work_in_progress.Sextad
hashCode.
hashCode() - Method in class edu.cmu.tetrad.sem.ParameterPair
hashCode.
hashCode() - Method in class edu.cmu.tetrad.sem.SemEvidence
hashCode.
hashCode() - Method in class edu.cmu.tetrad.sem.SemManipulation
hashCode.
hashCode() - Method in class edu.cmu.tetrad.sem.SemProposition
Calculates the hash code for this object.
hashCode() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedFactor
Probably should recheck this later.
hashCode() - Method in class edu.cmu.tetrad.util.Version
hashCode.
HasKnowledge - Interface in edu.cmu.tetrad.algcomparison.utils
Stores a knowledge object.
hasMoreTokens() - Method in class edu.cmu.tetrad.data.RegexTokenizer
hasMoreTokens.
hasNext() - Method in class edu.cmu.tetrad.search.utils.DagInCpcagIterator
Returns true just in case there is still a DAG remaining in the enumeration of DAGs for this CPDAG.
hasNext() - Method in class edu.cmu.tetrad.search.utils.DagIterator
Returns true just in case there is still a DAG remaining in the enumeration of DAGs for this pattern.
hasNext() - Method in class edu.cmu.tetrad.util.CombinationIterator
hasNext.
hasNoEvidence(int) - Method in class edu.cmu.tetrad.bayes.Evidence
hasNoEvidence.
HasParameters - Interface in edu.cmu.tetrad.algcomparison.utils
Tags a gadget as having parameters
HasParameterValues - Interface in edu.cmu.tetrad.algcomparison.utils
Tags a gadget as having parameters values.
HasPenaltyDiscount - Interface in edu.cmu.tetrad.search.utils
Provides an interface for an algorithm can can get/set a value for penalty disoucnt.
Hbsms - Interface in edu.cmu.tetrad.search.work_in_progress
Interface for Bff (Heuristic Best Significant Model Search) algorithm.
HbsmsBeam - Class in edu.cmu.tetrad.search.work_in_progress
Heuristic Best Significant Model Search using a beam search.
HbsmsBeam(Graph, CovarianceMatrix, Knowledge) - Constructor for class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
Constructor for HbsmsBeam.
HbsmsBeam(Graph, DataSet, Knowledge) - Constructor for class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
Constructor for HbsmsBeam.
HbsmsBeam.Move - Class in edu.cmu.tetrad.search.work_in_progress
A move.
HbsmsBeam.Move.Type - Enum Class in edu.cmu.tetrad.search.work_in_progress
Types of moves the algorithm can make.
HbsmsBeam.Score - Class in edu.cmu.tetrad.search.work_in_progress
The score.
HbsmsGes - Class in edu.cmu.tetrad.search.work_in_progress
Heuristic Best Significant Model Search using the GES algorithm.
HbsmsGes(Graph, DataSet) - Constructor for class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
Constructor for HbsmsGes.
HbsmsGes.GraphWithPValue - Class in edu.cmu.tetrad.search.work_in_progress
A graph with a P value.
HbsmsGes.Score - Class in edu.cmu.tetrad.search.work_in_progress
The score of a model.
hermite1(int, double) - Static method in class edu.cmu.tetrad.util.StatUtils
Computes the (statitician's) Hermite polynomial of a given index and value.
hermite2(int, double) - Static method in class edu.cmu.tetrad.util.StatUtils
Computes the (physicis's) Hermite polynomial of a given index and value.
HEURISTIC_1 - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.PcHeuristicType
Sort nodes alphabetically.
HEURISTIC_2 - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.PcHeuristicType
Sort edges by p-value.
HEURISTIC_3 - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.PcHeuristicType
Sort edges in reverse order using p-values of associated independence facts.
Highest - Enum constant in enum class edu.pitt.dbmi.algo.resampling.ResamplingEdgeEnsemble
Choose an edge iff its prob.
histogram(List<Double>, double[]) - Static method in class edu.cmu.tetrad.simulation.GdistanceUtils
Calculates the histogram of a given list of input values based on thresholds.
Histogram - Class in edu.cmu.tetrad.data
Model for a conditional histogram for mixed continuous and discrete variables.
Histogram(DataSet, String, boolean) - Constructor for class edu.cmu.tetrad.data.Histogram
This histogram is for variables in a particular data set.
Hsim - Class in edu.cmu.tetrad.simulation
Hsim class.
Hsim(Dag, Set<Node>, DataSet) - Constructor for class edu.cmu.tetrad.simulation.Hsim
Constructor for Hsim.
HsimAutoC - Class in edu.cmu.tetrad.simulation
Created by Erich on 3/28/2016.
HsimAutoC(DataSet) - Constructor for class edu.cmu.tetrad.simulation.HsimAutoC
Constructor for HsimAutoC.
HsimAutoC(String, char) - Constructor for class edu.cmu.tetrad.simulation.HsimAutoC
Constructor for HsimAutoC.
HsimAutoRun - Class in edu.cmu.tetrad.simulation
Created by Erich on 3/28/2016.
HsimAutoRun(DataSet) - Constructor for class edu.cmu.tetrad.simulation.HsimAutoRun
Constructor for HsimAutoRun.
HsimAutoRun(String, char) - Constructor for class edu.cmu.tetrad.simulation.HsimAutoRun
Constructor for HsimAutoRun.
HsimCompareRepeat - Class in edu.cmu.tetrad.simulation
Created by Erich on 7/15/2016.
HsimContinuous - Class in edu.cmu.tetrad.simulation
Created by Erich on 3/27/2016.
HsimContinuous(Dag, Set<Node>, DataSet) - Constructor for class edu.cmu.tetrad.simulation.HsimContinuous
Constructor for HsimContinuous.
HsimEvalFromData - Class in edu.cmu.tetrad.simulation
Created by ekummerfeld on 1/26/2017.
HsimRepeatAC - Class in edu.cmu.tetrad.simulation
Created by Erich on 4/29/2016.
HsimRepeatAC(DataSet) - Constructor for class edu.cmu.tetrad.simulation.HsimRepeatAC
Constructor for HsimRepeatAC.
HsimRepeatAC(String, char) - Constructor for class edu.cmu.tetrad.simulation.HsimRepeatAC
Constructor for HsimRepeatAC.
HsimRepeatAuto - Class in edu.cmu.tetrad.simulation
Created by Erich on 3/28/2016.
HsimRepeatAutoRun - Class in edu.cmu.tetrad.simulation
Created by Erich on 4/29/2016.
HsimRepeatAutoRun(DataSet) - Constructor for class edu.cmu.tetrad.simulation.HsimRepeatAutoRun
Constructor for HsimRepeatAutoRun.
HsimRepeatAutoRun(String, char) - Constructor for class edu.cmu.tetrad.simulation.HsimRepeatAutoRun
Constructor for HsimRepeatAutoRun.
HsimRobustCompare - Class in edu.cmu.tetrad.simulation
generate data from random graph, generated from parameters.
HsimRun - Class in edu.cmu.tetrad.simulation
Created by Erich on 3/28/2016.
HsimSchedule - Class in edu.cmu.tetrad.simulation
Created by Erich on 4/29/2016.
HsimStudy - Class in edu.cmu.tetrad.simulation
Created by Erich on 3/28/2016.
HsimStudyAuto - Class in edu.cmu.tetrad.simulation
Created by Erich on 3/28/2016.
HsimUtils - Class in edu.cmu.tetrad.simulation
Created by Erich on 4/22/2016.
HsimUtils() - Constructor for class edu.cmu.tetrad.simulation.HsimUtils
Constructor for HsimUtils.
HungarianAlgorithm - Class in edu.cmu.tetrad.search.utils
Provides an implemetation of the Kuhn–Munkres assignment algorithm of the year 1957.
HungarianAlgorithm(double[][]) - Constructor for class edu.cmu.tetrad.search.utils.HungarianAlgorithm
Trying to find lowest-cost assignment.
hybridsimulate() - Method in class edu.cmu.tetrad.simulation.Hsim
hybridsimulate.
hybridsimulate() - Method in class edu.cmu.tetrad.simulation.HsimContinuous
hybridsimulate.

I

IA - Static variable in class edu.cmu.tetrad.util.Params
Constant IA="ia"
Iamb - Class in edu.cmu.tetrad.search.work_in_progress
Implements IAMB.
Iamb(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Iamb
Constructs a new search.
IambnPc - Class in edu.cmu.tetrad.search.work_in_progress
Created by IntelliJ IDEA.
IambnPc(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IambnPc
Constructs a new search.
IcaLingam - Class in edu.cmu.tetrad.algcomparison.algorithm.continuous.dag
IcaLingam class implements the Algorithm and ReturnsBootstrapGraphs interface.
IcaLingam - Class in edu.cmu.tetrad.search
Implements the ICA-LiNGAM algorithm.
IcaLingam() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingam
Constructs a new instance of the IcaLingam algorithm.
IcaLingam() - Constructor for class edu.cmu.tetrad.search.IcaLingam
Constructor.
IcaLingD - Class in edu.cmu.tetrad.algcomparison.algorithm.continuous.dag
IcaLingD is an implementation of the Algorithm interface that performs the ICA-LiNG-D algorithm for discovering causal models for the linear non-Gaussian case where the underlying model might be cyclic.
IcaLingD - Class in edu.cmu.tetrad.search
Implements the ICA-LiNG-D algorithm as well as a some auxiliary methods for ICA-LiNG-D and ICA-LiNGAM.
IcaLingD() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingD
Constructs a new instance of the IcaLingD algorithm.
IcaLingD() - Constructor for class edu.cmu.tetrad.search.IcaLingD
Constructor.
IcaResult(Matrix, Matrix, Matrix, Matrix) - Constructor for class edu.cmu.tetrad.search.FastIca.IcaResult
Constructs an instance of the IcaResult class, taking as arguments the four matrices that are the result of the Fast ICA algorithm.
ICovarianceMatrix - Interface in edu.cmu.tetrad.data
Interface for covariance matrices.
Ida - Class in edu.cmu.tetrad.search
Implements the IDA algorithm.
Ida(DataSet, Graph, List<Node>) - Constructor for class edu.cmu.tetrad.search.Ida
Constructor.
Ida.NodeEffects - Class in edu.cmu.tetrad.search
Gives a list of nodes (parents or children) and corresponding minimum effects for the IDA algorithm.
IdaAverageSquaredDistance - Class in edu.cmu.tetrad.algcomparison.statistic
The IDA average squared distance.
IdaAverageSquaredDistance(SemIm) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.IdaAverageSquaredDistance
The IDA Average Squared Distance.
IdaCheck - Class in edu.cmu.tetrad.search
This calculates total effects and absolute total effects for an MPDAG G for all pairs distinct (x, y) of variables, where the total effect is obtained by regressing y on x ∪ S and reporting the regression coefficient.
IdaCheck(Graph, DataSet, SemIm) - Constructor for class edu.cmu.tetrad.search.IdaCheck
Constructs a new IDA check for the given MPDAG and data set.
IdaCheckAvgMaxSquaredDiffEstTrue - Class in edu.cmu.tetrad.algcomparison.statistic
IdaCheckAvgMaxSquaredDiffEstTrue calculates the average maximum squared difference between the estimated and true values for a given data model and graphs.
IdaCheckAvgMaxSquaredDiffEstTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMaxSquaredDiffEstTrue
Calculates the average maximum squared difference between the estimated and true values for a given data model and graphs.
IdaCheckAvgMinSquaredDiffEstTrue - Class in edu.cmu.tetrad.algcomparison.statistic
Represents a statistic that calculates the average minimum squared difference between the estimated and true values for a given data model and graphs.
IdaCheckAvgMinSquaredDiffEstTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMinSquaredDiffEstTrue
Calculates the average minimum squared difference between the estimated and true values for a given data model and graphs.
IdaCheckAvgSquaredDifference - Class in edu.cmu.tetrad.algcomparison.statistic
IdaCheckAvgSquaredDifference is a class that implements the Statistic interface.
IdaCheckAvgSquaredDifference() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgSquaredDifference
IdaCheckAvgSquaredDifference is a class that implements the Statistic interface.
IdaMaximumSquaredDifference - Class in edu.cmu.tetrad.algcomparison.statistic
IdaMaximumSquaredDifference is a statistic that calculates the "IDA Average Maximum Squared Difference" between a true graph and an estimated graph.
IdaMaximumSquaredDifference(SemIm) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.IdaMaximumSquaredDifference
Initializes a new instance of the IdaMaximumSquaredDifference class.
IdaMinimumSquaredDifference - Class in edu.cmu.tetrad.algcomparison.statistic
IdaMinimumSquaredDifference is a statistic that calculates the "IDA Average Minimum Squared Difference" between a true graph and an estimated graph.
IdaMinimumSquaredDifference(SemIm) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.IdaMinimumSquaredDifference
Constructs an instance of the IdaMinimumSquaredDifference class with the specified SEM IM.
Identifiability - Class in edu.cmu.tetrad.bayes
Identifiability, based on RowSummingExactUpdater
Identifiability(BayesIm) - Constructor for class edu.cmu.tetrad.bayes.Identifiability
Constructs a new updater for the given Bayes net.
Identifiability(BayesIm, Evidence) - Constructor for class edu.cmu.tetrad.bayes.Identifiability
Constructor for Identifiability.
identity(int) - Static method in class edu.cmu.tetrad.util.Matrix
identity.
identity(int) - Static method in class edu.cmu.tetrad.util.MatrixUtils
identity.
identity(int) - Static method in class edu.cmu.tetrad.util.TetradAlgebra
identity.
IFas - Interface in edu.cmu.tetrad.search
Gives an interface for fast adjacency searches (i.e., PC adjacency searches).
igamma(double, double) - Static method in class edu.cmu.tetrad.util.StatUtils
Calculates the incomplete gamma function for two doubles
IGCI - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The IGCI rule.
IGFci - Class in edu.cmu.tetrad.search.work_in_progress
Instance-specific GFci given in Fattaneh Jabbari's dissertation (Pages 144-147)
IGFci(IndependenceTest, ISScore) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IGFci
Constructs an instance of IGFci with the provided independence test and score.
IGFci(IndependenceTest, ISScore, Graph) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IGFci
Constructs an instance of IGFci with the provided independence test, score, and population graph.
IGraphSearch - Interface in edu.cmu.tetrad.search
Gives an interface for a search method that searches and returns a graph.
Im - Interface in edu.cmu.tetrad.util
Tagging interface for instantiated models.
Images - Class in edu.cmu.tetrad.algcomparison.algorithm.multi
Wraps the IMaGES algorithm for continuous variables.
Images() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Constructor for Images.
Images(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Constructor for Images.
IMAGES_META_ALG - Static variable in class edu.cmu.tetrad.util.Params
Constant IMAGES_META_ALG="imagesMetaAlg"
ImagesBoss - Class in edu.cmu.tetrad.algcomparison.algorithm.multi
Wraps the IMaGES algorithm for continuous variables.
ImagesBoss() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Constructor for ImagesBoss.
ImagesBoss(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Constructor for ImagesBoss.
ImagesScore - Class in edu.cmu.tetrad.search.score
Implements a score to average results over multiple scores.
ImagesScore(List<Score>) - Constructor for class edu.cmu.tetrad.search.score.ImagesScore
Constructs an IMaGES score using the given list of individual scores.
IMbSearch - Interface in edu.cmu.tetrad.search
Gives an interface for Markov blanket searches.
ImpliedArrowOrientationRatioEst - Class in edu.cmu.tetrad.algcomparison.statistic
The Implied Arrow Orientation Ratio Est statistic calculates the ratio of the number of implied arrows to the number of arrows in unshielded colliders in the estimated graph.
ImpliedArrowOrientationRatioEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst
Constructs the statistic.
ImpliedArrowOrientationRatioEst2 - Class in edu.cmu.tetrad.algcomparison.statistic
The Implied Arrow Orientation Ratio Est statistic calculates the ratio of the number of implied arrows to the number of arrows in unshielded colliders in the estimated graph.
ImpliedArrowOrientationRatioEst2() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst2
Constructs the statistic.
impliedCovar(Matrix, Matrix) - Static method in class edu.cmu.tetrad.util.MatrixUtils
 
ImpliedOrientationRatioEst - Class in edu.cmu.tetrad.algcomparison.statistic
The Implied Arrow Orientation Ratio Est statistic calculates the ratio of the number of implied arrows to the number of arrows in unshielded colliders in the estimated graph.
ImpliedOrientationRatioEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ImpliedOrientationRatioEst
Constructs the statistic.
ImpliesLegalMag - Class in edu.cmu.tetrad.algcomparison.statistic
Implies Legal MAG
ImpliesLegalMag() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ImpliesLegalMag
Constructor for LegalPag.
INCLUDE_NEGATIVE_COEFS - Static variable in class edu.cmu.tetrad.util.Params
Constant INCLUDE_NEGATIVE_COEFS="includeNegativeCoefs"
INCLUDE_NEGATIVE_SKEWS_FOR_BETA - Static variable in class edu.cmu.tetrad.util.Params
Constant INCLUDE_NEGATIVE_SKEWS_FOR_BETA="includeNegativeSkewsForBeta"
INCLUDE_POSITIVE_COEFS - Static variable in class edu.cmu.tetrad.util.Params
Constant INCLUDE_POSITIVE_COEFS="includePositiveCoefs"
INCLUDE_POSITIVE_SKEWS_FOR_BETA - Static variable in class edu.cmu.tetrad.util.Params
Constant INCLUDE_POSITIVE_SKEWS_FOR_BETA="includePositiveSkewsForBeta"
INCLUDE_STRUCTURE_MODEL - Static variable in class edu.cmu.tetrad.util.Params
Constant INCLUDE_STRUCTURE_MODEL="include_structure_model"
incompleteCholeskyGramMatrix(List<Kernel>, DataSet, List<Node>, double) - Static method in class edu.cmu.tetrad.search.utils.KernelUtils
Approximates Gram matrix using incomplete Cholesky factorization
increment(int[], int) - Method in class edu.cmu.tetrad.util.MultiDimIntTable
Increments the value at the given coordinates by the specified amount, returning the new value.
independenceFact(Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
independenceFact.
IndependenceFact - Class in edu.cmu.tetrad.graph
Stores a triple (x, y, z) of nodes.
IndependenceFact(Node, Node, Node...) - Constructor for class edu.cmu.tetrad.graph.IndependenceFact
Constructor for IndependenceFact.
IndependenceFact(Node, Node, Set<Node>) - Constructor for class edu.cmu.tetrad.graph.IndependenceFact
Constructor for IndependenceFact.
independenceFactMsg(Node, Node, Set<Node>, double) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
independenceFactMsg.
IndependenceFacts - Class in edu.cmu.tetrad.data
Stores a list of independence facts.
IndependenceFacts() - Constructor for class edu.cmu.tetrad.data.IndependenceFacts
Constructor for IndependenceFacts.
IndependenceFacts(IndependenceFacts) - Constructor for class edu.cmu.tetrad.data.IndependenceFacts
Constructor for IndependenceFacts.
IndependenceFacts(Graph) - Constructor for class edu.cmu.tetrad.data.IndependenceFacts
Constructor for IndependenceFacts.
IndependenceResult - Class in edu.cmu.tetrad.search.test
Stores a single conditional independence result, e.g., whether X _||_ Y | Z1,...,Zn holds or does not, and the p-value of the test.
IndependenceResult(IndependenceFact, boolean, double, double) - Constructor for class edu.cmu.tetrad.search.test.IndependenceResult
Constructor.
IndependenceResult(IndependenceFact, boolean, double, double, boolean) - Constructor for class edu.cmu.tetrad.search.test.IndependenceResult
Constructor.
IndependenceTest - Interface in edu.cmu.tetrad.search
Gives an interface that can be implemented by classes that do conditional independence testing.
IndependenceTestDescriptions - Class in edu.cmu.tetrad.util
May 14, 2019 11:25:02 AM
IndependenceWrapper - Interface in edu.cmu.tetrad.algcomparison.independence
Interface that algorithm must implement.
independent - Enum constant in enum class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCInference.OP
The operation is independent.
INDEPENDENT - Enum constant in enum class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCCausalInference.OP
The operation is independent.
index(Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Return the index of v in the current permutation.
IndexedConnectivity - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Stores a "shapshot" of the indexedConnectivity of a lag graph, using indices rather than Strings to refer to factors.
IndexedConnectivity(LagGraph) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity
Constructs an indexed connectivity for the getModel state of the given lag graph, including all edges.
IndexedConnectivity(LagGraph, boolean) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity
Constructs an indexed connectivity for the getModel state of the given lag graph.
IndexedLagGraph - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Stores a "shapshot" of the indexedLagGraph of a lag graph, using indices rather than Strings to refer to factors.
IndexedLagGraph(LagGraph) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph
Constructs an indexed lag graph for the getModel state of the given lag graph, including all edges.
IndexedLagGraph(LagGraph, boolean) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph
Constructs an indexed lag graph for the getModel state of the given lag graph.
IndexedMatrix - Class in edu.cmu.tetrad.util
Indexed matrix.
IndexedMatrix(double[][]) - Constructor for class edu.cmu.tetrad.util.IndexedMatrix
Constructs a new IndexedMatrix for the given matrix.
IndexedParent - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Holds an ordered pair (index, lag) to represent a causal parent of a factor, where the factor at the given index is independently known.
IndexedParent(int, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedParent
Constructs a new index parent.
Indicator - Class in edu.cmu.tetrad.util.dist
Created by IntelliJ IDEA.
IndTestChiSquare - Class in edu.cmu.tetrad.search.test
Checks the conditional independence X _||_ Y | S, where S is a set of discrete variable, and X and Y are discrete variable not in S, by applying a conditional Chi Square test.
IndTestChiSquare(DataSet, double) - Constructor for class edu.cmu.tetrad.search.test.IndTestChiSquare
Constructs a new independence checker to check conditional independence facts for discrete data using a g square test.
IndTestConditionalCorrelation - Class in edu.cmu.tetrad.search.test
Checks conditional independence of variable in a continuous data set using a conditional correlation test for the nonlinear nonGaussian with the additive error case.
IndTestConditionalCorrelation(DataSet, double, double, int, int, double) - Constructor for class edu.cmu.tetrad.search.test.IndTestConditionalCorrelation
Constructs a new Independence test which checks independence facts based on the correlation data implied by the given data set (must be continuous).
IndTestConditionalGaussianLrt - Class in edu.cmu.tetrad.search.test
Performs a test of conditional independence X _||_ Y | Z1...Zn where all searchVariables are either continuous or discrete.
IndTestConditionalGaussianLrt(DataSet, double, boolean) - Constructor for class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Constructor.
IndTestCramerT - Class in edu.cmu.tetrad.search.work_in_progress
Checks conditional independence for continuous variables using Cramer's T-test formula (Cramer, Mathematical Methods of Statistics (1951), page 413).
IndTestCramerT(CorrelationMatrix, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.
IndTestCramerT(DataSet, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Constructs a new Independence test which checks independence facts based on the correlation matrix implied by the given data set (must be continuous).
IndTestCramerT(ICovarianceMatrix, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.
IndTestDegenerateGaussianLrt - Class in edu.cmu.tetrad.search.test
Implements a degenerate Gaussian score as a LRT.
IndTestDegenerateGaussianLrt(DataSet) - Constructor for class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Constructs the score using a covariance matrix.
IndTestDegenerateGaussianLrt.Ret - Class in edu.cmu.tetrad.search.test
Stores a return value for a likelihood--i.e., a likelihood value and the degrees of freedom for it.
IndTestFisherZ - Class in edu.cmu.tetrad.search.test
Checks conditional independence of variable in a continuous data set using Fisher's Z test.
IndTestFisherZ(DataSet, double) - Constructor for class edu.cmu.tetrad.search.test.IndTestFisherZ
Constructs a new Independence test which checks independence facts based on the correlation matrix implied by the given data set (must be continuous).
IndTestFisherZ(ICovarianceMatrix, double) - Constructor for class edu.cmu.tetrad.search.test.IndTestFisherZ
Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.
IndTestFisherZ(Matrix, List<Node>, double) - Constructor for class edu.cmu.tetrad.search.test.IndTestFisherZ
Constructs a new Fisher Z independence test with the listed arguments.
IndTestFisherZConcatenateResiduals - Class in edu.cmu.tetrad.search.test
Calculates independence from pooled residuals using the Fisher Z method.
IndTestFisherZConcatenateResiduals(List<DataSet>, double) - Constructor for class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
Constructor.
IndTestFisherZFisherPValue - Class in edu.cmu.tetrad.search.test
Calculates independence from multiple datasets from using the Fisher method of pooling independence results.
IndTestFisherZFisherPValue(List<DataSet>, double) - Constructor for class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Constructor.
IndTestFisherZPercentIndependent - Class in edu.cmu.tetrad.search.work_in_progress
Calculates independence from pooled residuals.
IndTestFisherZPercentIndependent(List<DataSet>, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Initializes an object of the class IndTestFisherZPercentIndependent.
IndTestFisherZRecursive - Class in edu.cmu.tetrad.search.work_in_progress
Checks conditional independence of variable in a continuous data set using Fisher's Z test.
IndTestFisherZRecursive(DataSet, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Constructs a new Independence test which checks independence facts based on the correlation matrix implied by the given data set (must be continuous).
IndTestFisherZRecursive(ICovarianceMatrix, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.
IndTestFisherZRecursive(Matrix, List<Node>, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Constructs a new Fisher Z independence test with the listed arguments.
IndTestFromString(String, DataSet, double) - Static method in class edu.pitt.csb.mgm.MixedUtils
Returns independence tests by name located in edu.cmu.tetrad.search and edu.pitt.csb.mgm also supports shorthand for LRT ("lrt) and t-tests ("tlin" for prefer linear (fastest) or "tlog" for prefer logistic)
IndTestGSquare - Class in edu.cmu.tetrad.search.test
Checks the conditional independence X _||_ Y | S, where S is a set of discrete variable, and X and Y are discrete variable not in S, by applying a conditional G Square test.
IndTestGSquare(DataSet, double) - Constructor for class edu.cmu.tetrad.search.test.IndTestGSquare
Constructs a new independence checker to check conditional independence facts for discrete data using a g square test.
IndTestHsic - Class in edu.cmu.tetrad.search.test
Checks the conditional independence X _||_ Y | S, where S is a set of continuous variable, and X and Y are discrete variable not in S, using the Hilbert-Schmidth Independence Criterion (HSIC), a kernel based nonparametric test for conditional independence.
IndTestHsic(DataSet, double) - Constructor for class edu.cmu.tetrad.search.test.IndTestHsic
Constructs a new HSIC Independence test.
IndTestHsic(Matrix, List<Node>, double) - Constructor for class edu.cmu.tetrad.search.test.IndTestHsic
Constructs a new HSIC Independence test.
IndTestIndependenceFacts - Class in edu.cmu.tetrad.search.test
Checks conditional independence against a list of conditional independence facts, manually entered.
IndTestIndependenceFacts(IndependenceFacts) - Constructor for class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
Constructor.
IndTestIod - Class in edu.cmu.tetrad.search
Checks independence results by listing all tests with those variables, testing each one, and returning the resolution of these test results.
IndTestIod(List<IndependenceTest>) - Constructor for class edu.cmu.tetrad.search.IndTestIod
Constructs a new pooled independence test from the given list of independence tests.
IndTestMixedMultipleTTest - Class in edu.cmu.tetrad.search.work_in_progress
Performs a test of conditional independence X _||_ Y | Z1...Zn where all searchVariables are either continuous or discrete.
IndTestMixedMultipleTTest(DataSet, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
Constructor for IndTestMixedMultipleTTest.
IndTestMnlrLr - Class in edu.cmu.tetrad.search.work_in_progress
Performs a test of conditional independence X _||_ Y | Z1...Zn where all searchVariables are either continuous or discrete.
IndTestMnlrLr(DataSet, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestMnlrLr
Constructs a new independence test for the given data set and significance level.
IndTestMulti - Class in edu.cmu.tetrad.search.test
A class that represents a pooled independence test for multiple data sets.
IndTestMulti(List<IndependenceTest>, ResolveSepsets.Method) - Constructor for class edu.cmu.tetrad.search.test.IndTestMulti
Constructs a new pooled independence test for the given data sets.
IndTestMultinomialLogisticRegression - Class in edu.cmu.tetrad.search.work_in_progress
Performs a test of conditional independence X _||_ Y | Z1...Zn where all searchVariables are either continuous or discrete.
IndTestMultinomialLogisticRegression(DataSet, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
Constructor for IndTestMultinomialLogisticRegression.
IndTestMultinomialLogisticRegressionWald - Class in edu.pitt.csb.mgm
Performs a test of conditional independence X _||_ Y | Z1...Zn where all searchVariables are either continuous or discrete.
IndTestMultinomialLogisticRegressionWald(DataSet, double, boolean) - Constructor for class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
Constructs a new instance of IndTestMultinomialLogisticRegressionWald with the specified parameters.
IndTestMvpLrt - Class in edu.cmu.tetrad.search.test
Performs a test of conditional independence X _||_ Y | Z1...Zn where all variables are either continuous or discrete.
IndTestMvpLrt(DataSet, double, int, boolean) - Constructor for class edu.cmu.tetrad.search.test.IndTestMvpLrt
Constructor.
IndTestPositiveCorr - Class in edu.cmu.tetrad.search.work_in_progress
Checks conditional independence of variable in a continuous data set using Fisher's Z test.
IndTestPositiveCorr(DataSet, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Constructs a new Independence test which checks independence facts based on the correlation matrix implied by the given data set (must be continuous).
IndTestProbabilistic - Class in edu.cmu.tetrad.search.test
Uses BCInference by Cooper and Bui to calculate probabilistic conditional independence judgments.
IndTestProbabilistic(DataSet) - Constructor for class edu.cmu.tetrad.search.test.IndTestProbabilistic
Initializes the test using a discrete data sets.
IndTestRegression - Class in edu.cmu.tetrad.search.test
Checks independence of X _||_ Y | Z for variables X and Y and list Z of variables by regressing X on {Y} U Z and testing whether the coefficient for Y is zero.
IndTestRegression(DataSet, double) - Constructor for class edu.cmu.tetrad.search.test.IndTestRegression
Constructs a new Independence test which checks independence facts based on the correlation matrix implied by the given data set (must be continuous).
IndTestScore - Class in edu.cmu.tetrad.search.score
Gives a method of interpreting a test as a score.
IndTestScore(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.score.IndTestScore
Constructs the score using a covariance matrix.
IndTestSepsetDci - Class in edu.cmu.tetrad.search.work_in_progress
Checks independence facts for variables associated with a sepset by simply querying the sepset
IndTestSepsetDci(SepsetMapDci, List<Node>) - Constructor for class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
Constructs a new independence test that returns d-separation facts for the given graph as independence results.
indTestSubset(List<Node>) - Method in interface edu.cmu.tetrad.search.IndependenceTest
Returns an Independence test for a sublist of the variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.IndTestIod
Calculates the independence test for a subset of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Checks conditional independence between variables in a subset.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalCorrelation
Constructs a new Independence test which checks independence facts based on the correlation data implied by the given data set (must be continuous).
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
This method returns an instance of the IndependenceTest interface that can test the independence of a subset of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Subsets the variables used in the independence test.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Creates a new independence test instance for a subset of the variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
Returns an Independence test for a sublist of the variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Returns an Independence test for a sublist of the variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Performs an independence test on a subset of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Subset of variables for independence testing.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
Returns an IndependenceTest object for a sublist of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestMulti
Returns an Independence test for a sublist of the variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestMvpLrt
Returns an Independence test for a sublist of the variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Returns an Independence test for a sublist of the variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestRegression
Performs an independence test for a sublist of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Determines independence between variables in a given subset.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.Kci
 
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.MsepTest
Conducts an independence test on a subset of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Tests the independence between variables in a given sublist.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
This method performs an independence test based on a given sublist of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Performs an independence test on a subset of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Returns an Independence test for a sublist of the variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
 
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMnlrLr
This method returns an independence test for a sublist of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
Performs an independence test for a sublist of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Performs an independence test on a subset of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
Determines independence between a subset of variables.
indTestSubset(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
Returns an Independence test for a sublist of the variables.
indTestSubset(List<Node>) - Method in class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
Tests the conditional independence between two variables given a sublist of variables.
IndTestTrekSep - Class in edu.cmu.tetrad.search.test
Checks d-separations in a structural model using t-separations over indicators.
IndTestTrekSep(ICovarianceMatrix, double, List<List<Node>>, List<Node>) - Constructor for class edu.cmu.tetrad.search.test.IndTestTrekSep
Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.
inferFunction(int, SortedSet<ItkPredictorSearch.Gene>) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch
inferFunction.
INFIX - Enum constant in enum class edu.cmu.tetrad.calculator.expression.ExpressionDescriptor.Position
The expression can occur in the infix position.
info(String) - Method in class edu.cmu.tetrad.util.LogUtils
info.
INITIAL_GRAPH - Enum constant in enum class edu.cmu.tetrad.search.LvLite.START_WITH
Starts with an initial CPDAG over the variables of the independence test that is given in the constructor.
initialize() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Initializes the history array.
initialize(double[][]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasalInitializer
Sets the expression of each unregulated gene in the given history at time step 0 to a random value drawn from N(basalExpression, initStDev), sets the expression level at time step 0 of each regulated gene to zero, and then copies the values at history[0][j] to history[i][j] for all i > 0 less than the maximum time lag.
initialize(double[][]) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.Initializer
Initializes a history array.
initialize(LagGraph) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.GraphInitializer
Randomizes the given lag graph--in other words, chooses random edges for the graph according to a particlar scheme (see instantiations).
initialize(LagGraph) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PreviousStepOnly
Randomizes the given lag graph--in other words, chooses random edges for the graph according to a particlar scheme (see instantiations).
initialize(LagGraph) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.SimpleRandomizer
Randomizes the given lag graph--in other words, chooses random edges for the graph according to a particlar scheme (see instantiations).
INITIALIZE_FROM_DATA - Enum constant in enum class edu.cmu.tetrad.sem.StandardizedSemIm.Initialization
Initialize the SEM from data
Initializer - Interface in edu.cmu.tetrad.study.gene.tetrad.gene.history
Initializes a history array.
initializeValues() - Method in class edu.cmu.tetrad.sem.SemIm
Iterates through all freeParameters, picking values for them from the distributions that have been set for them.
innerProduct(double[], double[]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
innerProduct.
IntAveDataSetProbs - Class in edu.cmu.tetrad.bayes
Estimates probabilities directly from data on the fly using maximum likelihood method, with the exception that if rows do not exist in the data satisfying a required condition because certain values are unattested, an attempt is made to remove each relevant column in turn, record the estimated probability with column removed from the condition (if it is defined), and then return the average over the estimated probabilities calculated this way.
IntAveDataSetProbs(DataSet) - Constructor for class edu.cmu.tetrad.bayes.IntAveDataSetProbs
Creates a cell count table for the given data set.
IntDataBox - Class in edu.cmu.tetrad.data
Stores a 2D array of integer data.
IntDataBox(int[][]) - Constructor for class edu.cmu.tetrad.data.IntDataBox
Constructs a new data box using the given 2D short data array as data.
IntDataBox(int, int) - Constructor for class edu.cmu.tetrad.data.IntDataBox
Constructs an 2D short array consisting entirely of missing values (-99).
Integrator - Class in edu.cmu.tetrad.util
Integrates under a function from one endpoint to another.
InterIamb - Class in edu.cmu.tetrad.search.work_in_progress
Implements the Inter-IAMB algorithm.
InterIamb(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.work_in_progress.InterIamb
Constructs a new search.
intersection() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Checks if intersection holds--e.g., (X ⊥⊥ Y | (Z ∪ W)) ∧ (X ⊥⊥ W | (Z ∪ Y)) ==> X ⊥⊥ (Y ∪ W) |Z
INTERVAL_BETWEEN_RECORDINGS - Static variable in class edu.cmu.tetrad.util.Params
Constant INTERVAL_BETWEEN_RECORDINGS="intervalBetweenRecordings"
INTERVAL_BETWEEN_SHOCKS - Static variable in class edu.cmu.tetrad.util.Params
Constant INTERVAL_BETWEEN_SHOCKS="intervalBetweenShocks"
INTERVENTION_STATUS - Enum constant in enum class edu.cmu.tetrad.graph.NodeVariableType
The node variable type is intervened on with a specific status, such as treatment or control.
INTERVENTION_VALUE - Enum constant in enum class edu.cmu.tetrad.graph.NodeVariableType
The node variable type is intervened on with a specific value.
inverse() - Method in class edu.cmu.tetrad.util.Matrix
Returns the inverse of the matrix.
inverse(double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Calculates the inverse of a given matrix.
InverseCorrelation - Class in edu.cmu.tetrad.search.work_in_progress
Returns edges whose entries in the precision matrix exceed a certain threshold.
InverseCorrelation(DataSet, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.InverseCorrelation
Constructor for InverseCorrelation.
inverseCumulativeProbability(double) - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Calculates the inverse cumulative probability of a given point.
invoke(boolean, double) - Method in class edu.cmu.tetrad.search.test.TopEigenvalues
Performs eigendecomposition on a given matrix and optionally stores the top eigenvalues and (optionaly) eigenvectors.
invVech(double[]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
invVech.
Ion - Class in edu.cmu.tetrad.search.work_in_progress
Implements the ION (Integration of Overlapping Networks) algorithm for distributed causal inference.
Ion(List<Graph>) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Ion
Constructs a new instance of the ION search from the input PAGs
IonHittingSet - Class in edu.cmu.tetrad.search.work_in_progress
Provides a static method which implements a correct version of Reiter's hitting set algorithm as described by Greiner, Smith, and Wilkerson in "A Correction to the Algorithm in Reiter's Theory of Diagnosis" Artificial Intellegence 41 (1989) (see for detailed specification).
IPEN - Static variable in class edu.cmu.tetrad.util.Params
Constant IPEN="ipen"
IPurify - Interface in edu.cmu.tetrad.search.utils
Provides an interface for Purify algorithm.
IS - Static variable in class edu.cmu.tetrad.util.Params
Constant IS="is"
isAccommodateNewCategories() - Method in class edu.cmu.tetrad.data.DiscreteVariable
isAccommodateNewCategories.
isAcyclic(Matrix) - Method in class edu.cmu.tetrad.search.IcaLingam
Determines whether a BHat matrix parses to an acyclic graph.
isAdjacentTo(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Determines whether two nodes are adjacent in the graph.
isAdjacentTo(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
isAdjacentTo.
isAdjacentTo(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
isAdjacentTo.
isAdjacentTo(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
isAdjacentTo.
isAdjacentTo(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
isAdjacentTo.
isAdjacentTo(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Determines whether two nodes are adjacent in the graph.
isAllowed(int, int) - Method in class edu.cmu.tetrad.bayes.Proposition
isAllowed.
isAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Determines if a triple of nodes is ambiguous.
isAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
States whether r-s-r is an underline triple or not.
isAmbiguousTriple(Node, Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
States whether r-s-r is an underline triple or not.
isAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
States whether r-s-r is an underline triple or not.
isAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
States whether r-s-r is an underline triple or not.
isAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Checks whether a triple of nodes is ambiguous.
isAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Underlines
States whether r-s-r is an underline triple or not.
isAncestor(Node, Set<Node>) - Method in class edu.cmu.tetrad.graph.Paths
Return true if b is an ancestor of any node in z
isAncestorOf(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Determines whether one node is an ancestor of another.
isAncestorOf(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Determines whether one node is an ancestor of another.
isAncestorOf(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
isAncestorOf.
isAncestorOf(Node, Node) - Method in class edu.cmu.tetrad.graph.Paths
Determines whether one node is an ancestor of another.
isAntilogCalculated() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns true iff the antilog of each expression level should be calculated.
isAntilogCalculated() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
isAntilogCalculated.
isApplyR1() - Method in class edu.cmu.tetrad.search.Ccd
Returns true iff the R1 rule should be applied.
isArrowheadAllowed(Node, Node, Graph, Knowledge) - Static method in class edu.cmu.tetrad.search.utils.FciOrient
Determines whether an arrowhead is allowed between two nodes in a graph, based on specific conditions.
isArrowheadAllowed(Object, Object, Knowledge) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Checks if an arrowhead is allowed by background knowledge.
isArrowheadAllowed1(Node, Node, Knowledge) - Static method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
isArrowheadAllowed1.
isArrowheadAllowed1(Node, Node, Knowledge) - Static method in class edu.cmu.tetrad.search.work_in_progress.VcPc
isArrowheadAllowed1.
ISBDeuScore - Class in edu.cmu.tetrad.search.work_in_progress
Added by Fattaneh Calculates the Instance-Specific BDeu score.
ISBDeuScore(DataSet, DataSet) - Constructor for class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Initializes the ISBDeuScore with the given dataset and test case.
ISBicScore - Class in edu.cmu.tetrad.search.work_in_progress
A class representing the ISBicScore, which calculates BIC scores for a Bayesian network considering different structural changes and their impacts using an information-sharing mechanism.
ISBicScore(DataSet, DataSet) - Constructor for class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Constructs an ISBicScore instance with the provided data sets.
isBidirectedEdge(Edge) - Static method in class edu.cmu.tetrad.graph.Edges
isBidirectedEdge.
isBinary(DataSet, int) - Static method in class edu.cmu.tetrad.data.DataUtils
States whether the given column of the given data set is binary.
isBoundsEnforced() - Method in class edu.cmu.tetrad.bayes.DirichletDataSetProbs
True iff bounds checking is performed on variable values indices.
isCanalyzing() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
Determines whether the getModel function is canalyzing, according to Kaufmann's definition in Oridins of Order: "I define as a canalyzing Boolean function any Boolean function having the property that it has at least one input having at least one value (1 or 0) which suffices to guarantee that the regulated element assumes a specific value (1 or 0)" (page 203-4).
isCanceled() - Method in class edu.cmu.tetrad.util.TaskManager
isCanceled.
isCategoryNamesDisplayed() - Method in class edu.cmu.tetrad.data.DiscreteVariable
isCategoryNamesDisplayed.
isCheckingCycles() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
isCheckingCycles.
isChildOf(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Checks if the given node1 is a child of node2 in the graph.
isChildOf(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
isChildOf.
isChildOf(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
isChildOf.
isChildOf(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
isChildOf.
isChildOf(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
isChildOf.
isChildOf(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Checks if a given node is a child of another node in the graph.
isClique(Collection<Node>, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Checks if the given set of nodes forms a clique in the specified graph.
isColinear(DataSet, boolean) - Static method in class edu.pitt.csb.mgm.MixedUtils
Check each pair of variables to see if correlation is 1.
isCompleteRuleSetUsed() - Method in class edu.cmu.tetrad.search.Cfci
Returns true if Zhang's complete rule set should be used, false if only R1-T1 (the rule set of the original FCI) should be used.
isCompleteRuleSetUsed() - Method in class edu.cmu.tetrad.search.SpFci
Returns whether the complete rule set is used.
isCompleteRuleSetUsed() - Method in class edu.cmu.tetrad.search.SvarFci
Returns whether Zhang's complete rule set is to be used.
isCompleteRuleSetUsed() - Method in class edu.cmu.tetrad.search.utils.DagToPag
isCompleteRuleSetUsed.
isCompleteRuleSetUsed() - Method in class edu.cmu.tetrad.search.utils.FciOrient
Checks if the complete rule set is being used.
isCompleteRuleSetUsed() - Method in class edu.cmu.tetrad.search.utils.TsDagToPag
isCompleteRuleSetUsed.
isCompleteRuleSetUsed() - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Checks if the complete rule set is being used in the IGFci algorithm.
isConditioned(int) - Method in class edu.cmu.tetrad.bayes.Proposition
isConditioned.
isConfoundingTrek(Graph, List<Node>, Node, Node) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Checks if the given trek in a graph is a confounding trek.
isConsistent(GraphChange) - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Consistency check, nonexhaustive, but catches the most blatant inconsistencies.
isContinuous() - Method in class edu.cmu.tetrad.data.BoxDataSet
isContinuous.
isContinuous() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
isContinuous.
isContinuous() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
isContinuous.
isContinuous() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
isContinuous.
isContinuous() - Method in interface edu.cmu.tetrad.data.DataModel
isContinuous.
isContinuous() - Method in class edu.cmu.tetrad.data.DataModelList
isContinuous.
isContinuous() - Method in interface edu.cmu.tetrad.data.DataSet
isContinuous.
isContinuous() - Method in class edu.cmu.tetrad.data.IndependenceFacts
isContinuous.
isContinuous() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
isContinuous.
isContinuous() - Method in class edu.cmu.tetrad.data.TimeSeriesData
isContinuous.
isCopyData() - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
isCopyData.
isCorrectBidirectedEdge(Edge, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Determines if the given bidirected edge has a latent confounder in the true graph--that is, whether for X <-> Y there is a latent node Z such that X <- (Z) -> Y.
isCoveringAdjacency(Graph, Graph, Node, Node) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Determines whether an edge between two nodes in the estimated graph is covering a collider or noncollider in the true graph.
isCyclic() - Method in interface edu.cmu.tetrad.sem.ISemIm
isCyclic.
isCyclic() - Method in class edu.cmu.tetrad.sem.SemIm
isCyclic.
isDag(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Determines if the given graph is a directed acyclic graph (DAG).
isDataFromFile() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
isDataFromFile.
isDefaultToKnowledgeLayout() - Method in class edu.cmu.tetrad.data.Knowledge
isDefaultToKnowledgeLayout.
isDefCollider(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Checks if there is a definite collider between three nodes in the graph.
isDefCollider(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Added by ekorber, 2004/6/9.
isDefCollider(Node, Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Added by ekorber, 2004/6/9.
isDefCollider(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Added by ekorber, 2004/6/9.
isDefCollider(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Added by ekorber, 2004/6/9.
isDefCollider(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Determines if there is a definite collider relationship between the given nodes.
isDefNoncollider(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Checks if three given nodes form a definite non-collider in a graph.
isDefNoncollider(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Added by ekorber, 2004/6/9.
isDefNoncollider(Node, Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Added by ekorber, 2004/6/9.
isDefNoncollider(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Added by ekorber, 2004/6/9.
isDefNoncollider(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Added by ekorber, 2004/6/9.
isDefNoncollider(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Determines if the given nodes form a definite noncollider in the graph.
isDemixed() - Method in class edu.cmu.tetrad.search.work_in_progress.Demixer
isDemixed.
isDependent() - Method in class edu.cmu.tetrad.search.test.IndependenceResult
Returns whether the fact fails to hold--i.e.
isDescendentOf(Node, Node) - Method in class edu.cmu.tetrad.graph.Paths
Determines whether one node is a descendent of another.
isDetermined(int[], double) - Method in class edu.cmu.tetrad.search.test.ChiSquareTest
Returns a judgment of whether a set of parent variables determines a child variables.
isDirected() - Method in class edu.cmu.tetrad.graph.Edge
isDirected.
isDirected(Node, Node) - Method in class edu.cmu.tetrad.graph.Paths
Checks if there is a directed edge from node1 to node2 in the graph.
isDirectedEdge(Edge) - Static method in class edu.cmu.tetrad.graph.Edges
isDirectedEdge.
isDiscrete() - Method in class edu.cmu.tetrad.data.BoxDataSet
isDiscrete.
isDiscrete() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
isDiscrete.
isDiscrete() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
isDiscrete.
isDiscrete() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
isDiscrete.
isDiscrete() - Method in interface edu.cmu.tetrad.data.DataModel
isDiscrete.
isDiscrete() - Method in class edu.cmu.tetrad.data.DataModelList
isDiscrete.
isDiscrete() - Method in interface edu.cmu.tetrad.data.DataSet
isDiscrete.
isDiscrete() - Method in class edu.cmu.tetrad.data.IndependenceFacts
isDiscrete.
isDiscrete() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
isDiscrete.
isDiscrete() - Method in class edu.cmu.tetrad.data.TimeSeriesData
isDiscrete.
isDisplayLogEnabled() - Method in class edu.cmu.tetrad.util.TetradLogger
States whether to display the log display.
isDoOrientation() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
isDoOrientation.
isDoOrientation() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
isDoOrientation.
isDoOrientation() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
isDoOrientation.
isDoubleMissingValue(double) - Static method in class edu.cmu.tetrad.data.ContinuousVariable
Determines whether the argument is equal to the missing value marker.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.BasisFunctionBicScore
Determines if the given bump value represents an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.BdeScore
Determines if an edge has an effect.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.BdeuScore
Determines whether the bump exceeds zero.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.DegenerateGaussianScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.EbicScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.GicScores
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.GraphScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.ImagesScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.IndTestScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.MvpScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.PoissonPriorScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in interface edu.cmu.tetrad.search.score.Score
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.score.ZsbScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Must be called directly after the corresponding scoring call.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Must be called directly after the corresponding scoring call.
isEffectEdge(double) - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Determines whether the edge has a significant effect based on the given bump value.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.work_in_progress.MnlrScore
Returns true iff the edge between x and y is an effect edge.
isEffectEdge(double) - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Returns true iff the edge between x and y is an effect edge.
isEffective() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
Determines whether each input parent has an influence on the outcome--that is, whether for each parent there is a combination of states for the other parents for which the function would be different if the given parent were true as opposed to false.
ISemIm - Interface in edu.cmu.tetrad.sem
An interface for SemIM's; see implementations.
isEmpty() - Method in class edu.cmu.tetrad.data.Clusters
isEmpty.
isEmpty() - Method in class edu.cmu.tetrad.data.DataModelList
isEmpty() - Method in class edu.cmu.tetrad.data.Knowledge
true if there is no background knowledge recorded.
isEmpty() - Method in class edu.cmu.tetrad.data.KnowledgeGroup
States whether this group is empty, that is there is no edges in it (Note there may be some partial information though).
isErrorEdge(Edge) - Static method in class edu.cmu.tetrad.graph.SemGraph
isErrorEdge.
isEstimated() - Method in interface edu.cmu.tetrad.sem.ISemIm
isEstimated.
isEstimated() - Method in class edu.cmu.tetrad.sem.SemIm
isEstimated.
isEventActive(String) - Method in class edu.cmu.tetrad.util.DefaultTetradLoggerConfig
States whether the event associated with the given id is active, that is whether it should be logged or not.
isEventActive(String) - Method in class edu.cmu.tetrad.util.TetradLogger.EmptyConfig
isEventActive.
isEventActive(String) - Method in interface edu.cmu.tetrad.util.TetradLoggerConfig
States whether the event associated with the given id is active, that is whether it should be logged or not.
isExogenous(Node) - Method in class edu.cmu.tetrad.graph.Dag
Checks whether a given node is exogenous.
isExogenous(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
isExogenous.
isExogenous(Node) - Method in interface edu.cmu.tetrad.graph.Graph
isExogenous.
isExogenous(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
isExogenous.
isExogenous(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
isExogenous.
isExogenous(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Checks if a given node is exogenous.
isFaithfulnessAssumed() - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
isFaithfulnessAssumed.
isFaithfulnessAssumed() - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Returns the faithfulness assumption status for the current instance.
isFdr() - Method in class edu.cmu.tetrad.search.Pcd
True iff the algorithm should be run with False Discovery Rate tests.
ISFges - Class in edu.cmu.tetrad.search.work_in_progress
GesSearch is an implementation of the GES algorithm, as specified in Chickering (2002) "Optimal structure identification with greedy search" Journal of Machine Learning Research.
ISFges(ISScore) - Constructor for class edu.cmu.tetrad.search.work_in_progress.ISFges
Construct a Score and pass it in here.
isFileLoggingEnabled() - Method in class edu.cmu.tetrad.util.TetradLogger
States whether file logging is enabled or not.
isFixed() - Method in class edu.cmu.tetrad.sem.Parameter
isFixed.
isFlatPrior() - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbsParams
isFlatPrior.
isForbidden(Node) - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
isForbidden.
isForbidden(String, String) - Method in class edu.cmu.tetrad.data.Knowledge
Determines whether the edge var1 --> var2 is forbidden.
isForbiddenByGroups(String, String) - Method in class edu.cmu.tetrad.data.Knowledge
Legacy.
isForbiddenByTiers(String, String) - Method in class edu.cmu.tetrad.data.Knowledge
Determines whether the edge var1 --> var2 is forbidden by the temporal tiers.
isGuaranteeCpdag() - Method in class edu.cmu.tetrad.search.Pcd
Returns whether the algorithm should prevent cycles during the search.
isGuaranteeCpdag() - Method in class edu.cmu.tetrad.search.utils.PcCommon
Checks if the current object guarantees a complete directed acyclic graph (CPDAG).
isGuaranteeCpdag() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Checks if guaranteeCpdag is set to true.
isGuaranteeCpdag() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
isMeekPreventCycles.
isHighlighted() - Method in class edu.cmu.tetrad.graph.Edge
isHighlighted.
isIa() - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
isIa.
isIncludeDishAndChipColumns() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
isIncludeDishAndChipColumns.
isIncludeDishAndChipVariables() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
isIncludeDishAndChipVariables.
isIncompatibleWith(VariableSource) - Method in class edu.cmu.tetrad.bayes.Evidence
Returna true just in case this evidence has a list of variables equal to those of the given variable source.
isIncomplete(int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns true iff the given node has a Double.NaN value in it.
isIncomplete(int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns true iff the given node has a Double.NaN value in it.
isIncomplete(int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Checks if the specified table has any incomplete rows.
isIncomplete(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns true iff the given node has a Double.NaN value in it.
isIncomplete(int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns true iff the given node has a Double.NaN value in it.
isIncomplete(int, int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns true iff the given row in the given node has a Double.NaN value in it.
isIncomplete(int, int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Returns true iff the given row in the given node has a Double.NaN value in it.
isIncomplete(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Checks if the specified row of a table is incomplete, i.e., if any of the columns have a NaN value.
isIncomplete(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Returns true iff the given row in the given node has a Double.NaN value in it.
isIncomplete(int, int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Returns true iff the given row in the given node has a Double.NaN value in it.
isIndep() - Method in class edu.cmu.tetrad.search.test.ChiSquareTest.Result
Returns whether the conditional independence holds or not.
isIndependent() - Method in class edu.cmu.tetrad.search.test.IndependenceResult
Returns true if the judgment is for independence, false if for dependence.
isIndependent(Node, Node, Node...) - Method in class edu.cmu.tetrad.data.IndependenceFacts
isIndependent.
isIndependent(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.data.IndependenceFacts
isIndependent.
isIndependent(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.ConditionalCorrelationIndependence
Determines whether two given nodes are independent given a set of conditioning nodes, and calculates a score.
isIndependent(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.DagSepsets
Checks if node d is independent of node c given the set of nodes in sepset.
isIndependent(Node, Node, Set<Node>) - Method in interface edu.cmu.tetrad.search.utils.SepsetProducer
Checks if node d is independent of node c given the set of nodes in sepset.
isIndependent(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetsGreedy
Checks if node d is independent of node c given the set of nodes in sepset.
isIndependent(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetsMaxP
Determines if two nodes are independent given a set of separating nodes.
isIndependent(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetsMinP
Determines if two nodes are independent given a set of separating nodes.
isIndependent(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetsPossibleMsep
Checks if node d is independent of node c given the set of nodes in sepset.
isIndependent(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetsSet
Checks if node d is independent of node c given the set of nodes in sepset.
isIndependentPooled(ResolveSepsets.Method, List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
Tests for independence using one of the pooled methods
isIndependentPooled(ResolveSepsetsDci.Method, List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Tests for independence using one of the pooled methods
isIndependentPooledAverage(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
Checks independence from pooled samples by taking the average p value
isIndependentPooledAverage(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Checks independence from pooled samples by taking the average p value
isIndependentPooledAverageTest(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
Checks independence from pooled samples by taking the average test statistic CURRENTLY ONLY WORKS FOR CHISQUARE TEST
isIndependentPooledAverageTest(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Checks independence from pooled samples by taking the average test statistic CURRENTLY ONLY WORKS FOR CHISQUARE TEST
isIndependentPooledFisher(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
Checks independence from pooled samples using Fisher's method.
isIndependentPooledFisher(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Checks independence from pooled samples using Fisher's method.
isIndependentPooledFisher2(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
Eliminates from considerations independence tests that cannot be evaluated (due to missing variables mainly).
isIndependentPooledFisher2(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Eliminates from considerations independence tests that cannot be evaluated (due to missing variables mainly).
isIndependentPooledMudholkerGeorge(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
Checks independence from pooled samples using Mudholker and George's method
isIndependentPooledMudholkerGeorge(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Checks independence from pooled samples using Mudholker and George's method
isIndependentPooledMudholkerGeorge2(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
The same as isIndepenentPooledMudholkerGeoerge, except that only available independence tests are used.
isIndependentPooledMudholkerGeorge2(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
The same as isIndepenentPooledMudholkerGeoerge, except that only available independence tests are used.
isIndependentPooledRandom(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
Checks independence from pooled samples by randomly selecting a p value
isIndependentPooledRandom(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Checks independence from pooled samples by randomly selecting a p value
isIndependentPooledStouffer(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
Checks independence from pooled samples using Stouffer et al.'s method
isIndependentPooledStouffer(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Checks independence from pooled samples using Stouffer et al.'s method
isIndependentPooledTippett(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
Checks independence from pooled samples using Tippett's method
isIndependentPooledTippett(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Checks independence from pooled samples using Tippett's method
isIndependentPooledWilkinson(List<IndependenceTest>, Node, Node, Set<Node>, int) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
Checks independence from pooled samples using Wilkinson's method
isIndependentPooledWilkinson(List<IndependenceTest>, Node, Node, Set<Node>, int) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Checks independence from pooled samples using Wilkinson's method
isIndependentPooledWorsleyFriston(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.ResolveSepsets
Checks independence from pooled samples using Worsley and Friston's method
isIndependentPooledWorsleyFriston(List<IndependenceTest>, Node, Node, Set<Node>) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Checks independence from pooled samples using Worsley and Friston's method
isInitializedRandomly() - Method in class edu.cmu.tetrad.sem.Parameter
isInitializedRandomly.
isInitSync() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns 'true' if cells in the simulation will be synchronized, 'false' if not.
isInitSync() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
isInitSync.
isInWhichTier(Node) - Method in class edu.cmu.tetrad.data.Knowledge
Returns the index of the tier of node if it's in a tier, otherwise -1.
isIpen() - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
isIpen.
isIs() - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
isIs.
isItr() - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
isItr.
isJointMarginalSupported() - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
isJointMarginalSupported.
isJointMarginalSupported() - Method in interface edu.cmu.tetrad.bayes.BayesUpdater
Returns the joint marginal probability of the given variables taking the given values, given the evidence.
isJointMarginalSupported() - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
isJointMarginalSupported.
isJointMarginalSupported() - Method in class edu.cmu.tetrad.bayes.Identifiability
isJointMarginalSupported.
isJointMarginalSupported() - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Returns the joint marginal probability of the given variables taking the given values, given the evidence.
isJointMarginalSupported() - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
isJointMarginalSupported.
isLatentVariableAlgorithmByAnnotation(Algorithm) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Checks if the provided algorithm is a latent variable algorithm by inspecting the associated annotation.
isLegalCpdag() - Method in class edu.cmu.tetrad.graph.Paths
Checks if the current graph is a legal CPDAG (completed partially directed acyclic graph).
isLegalDag() - Method in class edu.cmu.tetrad.graph.Paths
Checks if the graph passed as parameter is a legal directed acyclic graph (DAG).
isLegalFirstEdge(Node, Node) - Method in interface edu.cmu.tetrad.search.utils.LegalPairs
isLegalFirstEdge.
isLegalMag() - Method in class edu.cmu.tetrad.graph.Paths
Checks if the given graph is a legal mag.
isLegalMag() - Method in class edu.cmu.tetrad.search.utils.GraphSearchUtils.LegalMagRet
Returns whether the graph is a legal MAG.
isLegalMag(Graph, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Determines whether the given graph is a legal Mixed Ancestral Graph (MAG).
isLegalMpag() - Method in class edu.cmu.tetrad.graph.Paths
Checks if the given Maximal Ancestral Graph (MPAG) is legal.
isLegalMpdag() - Method in class edu.cmu.tetrad.graph.Paths
Checks if the given graph is a legal Maximal Partial Directed Acyclic Graph (MPDAG).
isLegalName(String) - Static method in class edu.cmu.tetrad.util.NamingProtocol
isLegalName.
isLegalPag() - Method in class edu.cmu.tetrad.graph.Paths
Checks if the given Directed Acyclic Graph (DAG) is a Legal Partial Ancestral Graph (PAG).
isLegalPag() - Method in class edu.cmu.tetrad.search.utils.GraphSearchUtils.LegalPagRet
Returns whether the graph is a legal PAG.
isLegalPag(Graph, Set<Node>) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Checks if the provided Directed Acyclic Graph (PAG) is a legal PAG.
isLegalPair(Node, Node, Node, List<Node>, List<Node>) - Method in interface edu.cmu.tetrad.search.utils.LegalPairs
isLegalPair.
isLog() - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
True iff log output should be produced.
isLogging() - Method in class edu.cmu.tetrad.util.TetradLogger
States whether the logger is turned on or not.
isManipulated(int) - Method in class edu.cmu.tetrad.bayes.Evidence
isManipulated.
isManipulated(int) - Method in class edu.cmu.tetrad.bayes.Manipulation
isManipulated.
isManipulated(int) - Method in class edu.cmu.tetrad.sem.SemEvidence
isManipulated.
isManipulated(int) - Method in class edu.cmu.tetrad.sem.SemManipulation
isManipulated.
isMConnectedTo(Node, Node, Set<Node>, boolean) - Method in class edu.cmu.tetrad.graph.Paths
Determmines whether x and y are d-connected given z.
isMConnectedTo(Node, Node, Set<Node>, Map<Node, Set<Node>>, boolean) - Method in class edu.cmu.tetrad.graph.Paths
Detemrmines whether x and y are d-connected given z.
isMConnectingPath(List<Node>, Set<Node>, boolean) - Method in class edu.cmu.tetrad.graph.Paths
Checks if the given path is an m-connecting path.
isMConnectingPath(List<Node>, Set<Node>, Map<Node, Set<Node>>, boolean) - Method in class edu.cmu.tetrad.graph.Paths
Checks if the given path is an m-connecting path.
isMeasuredDataSaved() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns 'true' if measured data is being saved out for the getModel simulation, 'false' if not.
isMeekPreventCycles() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
isMeekPreventCycles.
isMeekPreventCycles() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
isMeekPreventCycles.
isMeekPreventCycles() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
isMeekPreventCycles.
isMeekPreventCycles() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
isMeekPreventCycles.
isMissingValue(Object) - Method in class edu.cmu.tetrad.data.AbstractVariable
Tests whether the given value is the missing data marker.
isMissingValue(Object) - Method in class edu.cmu.tetrad.data.ContinuousVariable
Tests whether the given value is the missing data marker.
isMissingValue(Object) - Method in class edu.cmu.tetrad.data.DiscreteVariable
Tests whether the given value is the missing data marker.
isMissingValue(Object) - Method in interface edu.cmu.tetrad.data.Variable
Tests whether the given value is the missing data marker.
isMixed() - Method in class edu.cmu.tetrad.data.BoxDataSet
isMixed.
isMixed() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
isMixed.
isMixed() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
isMixed.
isMixed() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
isMixed.
isMixed() - Method in interface edu.cmu.tetrad.data.DataModel
isMixed.
isMixed() - Method in class edu.cmu.tetrad.data.DataModelList
isMixed.
isMixed() - Method in interface edu.cmu.tetrad.data.DataSet
isMixed.
isMixed() - Method in class edu.cmu.tetrad.data.IndependenceFacts
isMixed.
isMixed() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
isMixed.
isMixed() - Method in class edu.cmu.tetrad.data.TimeSeriesData
isMixed.
isMpdag() - Method in class edu.cmu.tetrad.search.MarkovCheck
Checks whether the given graph is a CPDAG (Completed Partially Directed Acyclic Graph).
isMSeparated(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.test.MsepTest
Auxiliary method to calculate msep(x, y | z) directly from nodes instead of from variables.
isMSeparatedFrom(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Determines whether x and y are d-separated given z.
isMSeparatedFrom(Node, Node, Set<Node>, boolean) - Method in class edu.cmu.tetrad.graph.Paths
Determines whether one n ode is d-separated from another.
isMSeparatedFrom(Node, Node, Set<Node>, Map<Node, Set<Node>>, boolean) - Method in class edu.cmu.tetrad.graph.Paths
Checks if two nodes are M-separated.
isNoData() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
isNoData.
isNondirectedEdge(Edge) - Static method in class edu.cmu.tetrad.graph.Edges
isNondirectedEdge.
isNull() - Method in class edu.cmu.tetrad.graph.Edge
isNull.
isOneEdgeFaithfulnessAssumed() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
isOneEdgeFaithfulnessAssumed.
isOnlyCanCauseNextTier(int) - Method in class edu.cmu.tetrad.data.Knowledge
isOnlyCanCauseNextTier.
isParallelized() - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
isParallelized.
isParameterBoundsEnforced() - Method in interface edu.cmu.tetrad.sem.ISemIm
isParameterBoundsEnforced.
isParameterBoundsEnforced() - Method in class edu.cmu.tetrad.sem.SemIm
isParameterBoundsEnforced.
isParameterizable(Node) - Method in class edu.cmu.tetrad.graph.Dag
Checks if the given node is parameterizable.
isParameterizable(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
isParameterizable.
isParameterizable(Node) - Method in interface edu.cmu.tetrad.graph.Graph
isParameterizable.
isParameterizable(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
isParameterizable.
isParameterizable(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
isParameterizable.
isParameterizable(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Checks if a node is parameterizable.
isParent(int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.BiolinguaDigraph
Returns true if node p is parent of node c.
isParentOf(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Determines if a given node is a parent of another node in the graph.
isParentOf(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Determines whether node1 is a parent of node2.
isParentOf(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Determines whether node1 is a parent of node2.
isParentOf(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Determines whether node1 is a parent of node2.
isParentOf(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Determines whether node1 is a parent of node2.
isParentOf(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Determines if a given node is a parent of another node in the graph.
isPartiallyOrientedEdge(Edge) - Static method in class edu.cmu.tetrad.graph.Edges
isPartiallyOrientedEdge.
isPermissibleCombination(int[]) - Method in class edu.cmu.tetrad.bayes.Proposition
isPermissibleCombination.
isPositiveDefinite(Matrix) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Return true if the given matrix is symmetric positive definite--that is, if it would make a valid covariance matrix.
isPossibleMsepSearchDone() - Method in class edu.cmu.tetrad.search.Cfci
Whether to do the discriminating path rule.
isRawDataSaved() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns true if raw data is being saved in the getModel simulation, false if not.
isRawDataSaved() - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
isRawDataSaved.
isRequired(Node) - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
isRequired.
isRequired(String, String) - Method in class edu.cmu.tetrad.data.Knowledge
Determines whether the edge var1 --> var2 is required.
isRequiredByGroups(String, String) - Method in class edu.cmu.tetrad.data.Knowledge
Legacy.
isSatisfyBackDoorCriterion(Graph, Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.graph.Paths
Check to see if a set of variables Z satisfies the back-door criterion relative to node x and node y.
isSaveCPDAGs() - Method in class edu.cmu.tetrad.algcomparison.Comparison
Checks if the CPDAGs are saved.
isSaveCPDAGs() - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
isSaveCPDAGs.
isSaveData() - Method in class edu.cmu.tetrad.algcomparison.Comparison
Returns the status of whether data is being saved or not.
isSaveGraphs() - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
isSaveGraphs.
isSavePags() - Method in class edu.cmu.tetrad.algcomparison.Comparison
Checks if the "savePags" variable is true or false.
isSavePags() - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
isSavePags.
ISScore - Interface in edu.cmu.tetrad.search.work_in_progress
Interface for a score suitable for FGES
isSelected(Node) - Method in class edu.cmu.tetrad.data.BoxDataSet
isSelected.
isSelected(Node) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Checks if the specified node is selected in the covariance matrix.
isSelected(Node) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Checks if the specified node is selected in the covariance matrix.
isSelected(Node) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Checks if the specified node is selected in the covariance matrix.
isSelected(Node) - Method in interface edu.cmu.tetrad.data.DataSet
isSelected.
isSelected(Node) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Checks if the specified node is selected in the covariance matrix.
isSelected(Node) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
isSelected.
isShowErrorTerms() - Method in class edu.cmu.tetrad.graph.SemGraph
isShowErrorTerms.
isShowUtilities() - Method in class edu.cmu.tetrad.algcomparison.Comparison
Checks if the utilities are currently being shown.
isShowUtilities() - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
isShowUtilities.
isSimulatedPositiveDataOnly() - Method in interface edu.cmu.tetrad.sem.ISemIm
isSimulatedPositiveDataOnly.
isSimulatedPositiveDataOnly() - Method in class edu.cmu.tetrad.sem.SemIm
isSimulatedPositiveDataOnly.
isSingular() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
isSingular.
isSortByUtility() - Method in class edu.cmu.tetrad.algcomparison.Comparison
Returns whether utility does the sorting.
isSortByUtility() - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
isSortByUtility.
isSquare() - Method in class edu.cmu.tetrad.util.Matrix
isSquare.
isSquare(double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
isSquare.
isStable(Matrix) - Static method in class edu.cmu.tetrad.search.IcaLingD
Whether the BHat matrix represents a stable model.
isSubtrek(List<Node>, List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.Dci
Determines whether one trek is a subtrek of another trek
isSupportConnected() - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Returns a boolean indicating whether the support of the distribution is connected or not.
isSupportLowerBoundInclusive() - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Deprecated.
This method is deprecated and will be removed in a future release.
isSupportUpperBoundInclusive() - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Deprecated.
This method is deprecated and will be removed in a future release.
isSymmetric(double) - Method in class edu.cmu.tetrad.util.Matrix
isSymmetric.
isSymmetric(double[][], double) - Static method in class edu.cmu.tetrad.util.MatrixUtils
isSymmetric.
isSymmetricFirstStep() - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Checks if the first step of the algorithm is symmetric.
isTabDelimitedTables() - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
isTabDelimitedTables.
isTierForbiddenWithin(int) - Method in class edu.cmu.tetrad.data.Knowledge
Checks whether it is the case that any variable is forbidden by any other variable within a given tier.
isTimeLagModel() - Method in class edu.cmu.tetrad.graph.Dag
isTimeLagModel.
isTimeLagModel() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
isTimeLagModel.
isTimeLagModel() - Method in interface edu.cmu.tetrad.graph.Graph
isTimeLagModel.
isTimeLagModel() - Method in class edu.cmu.tetrad.graph.LagGraph
isTimeLagModel.
isTimeLagModel() - Method in class edu.cmu.tetrad.graph.SemGraph
isTimeLagModel.
isTimeLagModel() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Checks if the model is based on time lag.
isTruthAdj() - Method in class edu.cmu.tetrad.algcomparison.statistic.utils.ArrowConfusion
Returns true if the truth graph is used to determine adjacency for arrowhead FP's.
isUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Determines if a triple of nodes is underlined.
isUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
States whether r-s-r is an underline triple or not.
isUnderlineTriple(Node, Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
States whether r-s-r is an underline triple or not.
isUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
States whether r-s-r is an underline triple or not.
isUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
States whether r-s-r is an underline triple or not.
isUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Checks whether a given triple (x, y, z) is an underline triple.
isUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Underlines
States whether r-s-r is an underline triple or not.
isUndirected(Node, Node) - Method in class edu.cmu.tetrad.graph.Paths
Checks if the edge between two nodes in the graph is undirected.
isUndirectedEdge(Edge) - Static method in class edu.cmu.tetrad.graph.Edges
isUndirectedEdge.
isUnshieldedCollider(Graph, Node, Node, Node) - Method in interface edu.cmu.tetrad.search.utils.R0R4Strategy
Determines if a given triple is an unshielded collider based on an examination of the data.
isUnshieldedCollider(Graph, Node, Node, Node) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyScoreBased
Checks if a collider is unshielded or not.
isUnshieldedCollider(Graph, Node, Node, Node) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Checks if a collider is unshielded or not.
isUnshieldedCollider(Node, Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.DagSepsets
isUnshieldedCollider.
isUnshieldedCollider(Node, Node, Node, int) - Method in interface edu.cmu.tetrad.search.utils.SepsetProducer
isUnshieldedCollider.
isUnshieldedCollider(Node, Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsGreedy
isUnshieldedCollider.
isUnshieldedCollider(Node, Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsMaxP
Determines if a node is an unshielded collider between two other nodes.
isUnshieldedCollider(Node, Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsMinP
Checks if a given collider node is unshielded between two other nodes.
isUnshieldedCollider(Node, Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsPossibleMsep
isUnshieldedCollider.
isUnshieldedCollider(Node, Node, Node, int) - Method in class edu.cmu.tetrad.search.utils.SepsetsSet
isUnshieldedCollider.
isValid() - Method in class edu.cmu.tetrad.search.test.ChiSquareTest.Result
Returns whether the result is valid or not.
isValid() - Method in class edu.cmu.tetrad.search.test.IndependenceResult
Returns whether the result is valid or not.
isVariableListEqual(int[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialTerm
Returns true iff the given variable list is equal to the variable list of this term.
isVerbose() - Method in class edu.cmu.tetrad.cluster.KMeans
isVerbose.
isVerbose() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
isVerbose.
isVerbose() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
isVerbose.
isVerbose() - Method in class edu.cmu.tetrad.search.Cfci
Whether verbose output (about independencies) is output.
isVerbose() - Method in class edu.cmu.tetrad.search.CompositeIndependenceTest
Returns true if the test prints verbose output.
isVerbose() - Method in class edu.cmu.tetrad.search.Fasd
Returns the current value of the verbose flag.
isVerbose() - Method in interface edu.cmu.tetrad.search.IndependenceTest
Returns true if the test prints verbose output.
isVerbose() - Method in class edu.cmu.tetrad.search.IndTestIod
Returns true if the test is verbose.
isVerbose() - Method in class edu.cmu.tetrad.search.Pcd
True iff the algorithm should be run with verbose output.
isVerbose() - Method in class edu.cmu.tetrad.search.Rfci
Returns whether verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.score.GicScores
Returns true if verbose output should be sent to out.
isVerbose() - Method in class edu.cmu.tetrad.search.score.IndTestScore
Returns true if verbose output should be sent to out.
isVerbose() - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns true if verbose output should be sent to out.
isVerbose() - Method in class edu.cmu.tetrad.search.SvarFci
Returns whether verbose output is to be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Checks if the verbosity flag is enabled.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalCorrelation
Returns true if verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Returns true iff verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Returns true iff verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Returns true iff verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
Return True if verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Returns True if verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Returns whether verbose output is enabled or not.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Determines if the verbose mode is enabled.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
Returns whether verbose output is to be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestMulti
Returns true if the test prints verbose output.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestMvpLrt
Returns whether verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Returns the verbose flag indicating whether verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestRegression
Returns true if the test prints verbose output.
isVerbose() - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Checks whether verbose output is enabled.
isVerbose() - Method in class edu.cmu.tetrad.search.test.Kci
Returns the value of the verbose flag.
isVerbose() - Method in class edu.cmu.tetrad.search.test.MsepTest
Returns True just in case verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Returns a boolean indicating whether verbose output is enabled.
isVerbose() - Method in class edu.cmu.tetrad.search.utils.SepsetsGreedy
Returns whether the object is in verbose mode.
isVerbose() - Method in class edu.cmu.tetrad.search.utils.SepsetsMaxP
Returns whether the object is in verbose mode.
isVerbose() - Method in class edu.cmu.tetrad.search.utils.SepsetsMinP
Returns whether the object is in verbose mode.
isVerbose() - Method in class edu.cmu.tetrad.search.utils.SepsetsPossibleMsep
isVerbose.
isVerbose() - Method in class edu.cmu.tetrad.search.utils.SepsetsSet
isVerbose.
isVerbose() - Method in class edu.cmu.tetrad.search.utils.TsDagToPag
True iff verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
isVerbose.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Checks if verbose output is enabled.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Determines if verbose output is enabled or disabled.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Returns the value of the verbose flag.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
isVerbose.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
Returns whether verbose output should be printed.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMnlrLr
Determines if the test prints verbose output.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
Returns true if the test prints verbose output.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Returns whether the verbose mode is enabled.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
isVerbose.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
Returns true if the test prints verbose output.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
isVerbose.
isVerbose() - Method in class edu.cmu.tetrad.search.work_in_progress.VcFas
isVerbose.
isVerbose() - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
isVerbose.
isVerbose() - Method in class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
Checks if the program is in verbose mode.
isViolatedBy(Graph) - Method in class edu.cmu.tetrad.data.Knowledge
isViolatedBy.
isWithoutReplacements() - Method in class edu.cmu.tetrad.data.BootstrapSampler
This method takes a dataset and a sample size and creates a new dataset containing that number of samples by
iterate() - Method in class edu.cmu.tetrad.bayes.FactoredBayesStructuralEM
This iterate2 method also uses BdeMetricCache but it uses the factorScoreMD method which can handle missing data and latent variables.
iterations() - Method in class edu.cmu.tetrad.cluster.KMeans
iterations.
iterator() - Method in class edu.pitt.isp.sverchkov.data.DataTableImpl
ItkPredictorSearch - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker
This class contains methods which implement the algorithm described in the paper " " by Ideker, Thorsen and Karp.
ItkPredictorSearch(int, int[][], String[]) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch
Constructor for ItkPredictorSearch.
ItkPredictorSearch.Gene - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker
A gene.
ITR - Static variable in class edu.cmu.tetrad.util.Params
Constant ITR="itr"

J

jointEntropy(int[], int[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealEvaluator
This method computes the joint entropy of two arrays.
jointEntropy(int[], int[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.LTestReveal
jointEntropy.
jointEntropy(int[], int[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealEvaluator
This method computes the joint entropy of two arrays.
jointEntropy(int[], int[][]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealEvaluator
jointEntropy.
jointEntropy(int[], int[][]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.LTestReveal
jointEntropy.
jointEntropy(int[], int[][]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealEvaluator
jointEntropy.
JOptionUtils - Class in edu.cmu.tetrad.util
Stores some utility items for displaying JOptionPane messages.
JsonUtils - Class in edu.cmu.tetrad.util
Dec 9, 2016 5:43:47 PM
JsonUtils() - Constructor for class edu.cmu.tetrad.util.JsonUtils
Constructor for JsonUtils.
JunctionTreeAlgorithm - Class in edu.cmu.tetrad.bayes
Junction Tree Algorithm.
JunctionTreeAlgorithm(BayesIm) - Constructor for class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
Constructor for JunctionTreeAlgorithm.
JunctionTreeAlgorithm(Graph, DataModel) - Constructor for class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
Constructor for JunctionTreeAlgorithm.
JunctionTreeUpdater - Class in edu.cmu.tetrad.bayes
Jan 21, 2020 11:03:09 AM
JunctionTreeUpdater(BayesIm) - Constructor for class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Constructor for JunctionTreeUpdater.
JunctionTreeUpdater(BayesIm, Evidence) - Constructor for class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Constructor for JunctionTreeUpdater.
JUSTIFIED - Enum constant in enum class edu.cmu.tetrad.util.TextTable.Delimiter
Constant JUSTIFIED

K

kamadaKawaiLayout(Graph, boolean, double, double, double) - Static method in class edu.cmu.tetrad.graph.LayoutUtil
kamadaKawaiLayout.
KamadaKawaiLayout(Graph) - Constructor for class edu.cmu.tetrad.graph.LayoutUtil.KamadaKawaiLayout
Constructs a new Kamada-Kawai layout for the given graph.
Kci - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for KCI test.
Kci - Class in edu.cmu.tetrad.search.test
Gives an implementation of the Kernel Independence Test (KCI) by Kun Zhang, which is a general test of conditional independence.
Kci() - Constructor for class edu.cmu.tetrad.algcomparison.independence.Kci
`Kci` constructor.
Kci(DataSet, double) - Constructor for class edu.cmu.tetrad.search.test.Kci
Constructor.
KCI_ALPHA - Static variable in class edu.cmu.tetrad.util.Params
Constant KCI_ALPHA="kciAlpha"
KCI_CUTOFF - Static variable in class edu.cmu.tetrad.util.Params
Constant KCI_CUTOFF="kciCutoff"
KCI_EPSILON - Static variable in class edu.cmu.tetrad.util.Params
Constant KCI_EPSILON="kciEpsilon"
KCI_NUM_BOOTSTRAPS - Static variable in class edu.cmu.tetrad.util.Params
Constant KCI_NUM_BOOTSTRAPS="kciNumBootstraps"
KCI_USE_APPROXIMATION - Static variable in class edu.cmu.tetrad.util.Params
Constant KCI_USE_APPROXIMATION="kciUseApproximation"
Kci.EigenReturn - Record Class in edu.cmu.tetrad.search.test
A record representing the result of an eigenvalue decomposition.
Kci.KernelType - Enum Class in edu.cmu.tetrad.search.test
Represents the type of kernel to be used in a computation.
kendallsTau(double[], double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
kendallsTau.
kernel(double) - Method in class edu.cmu.tetrad.search.Lofs
Calculates the kernel value for a given input.
Kernel - Interface in edu.cmu.tetrad.search.utils
Gives an implemented that is implemented by classes that evaluate scalar valued kernels
KERNEL_REGRESSION_SAMPLE_SIZE - Static variable in class edu.cmu.tetrad.util.Params
Constant KERNEL_REGRESSION_SAMPLE_SIZE="kernelRegressionSampleSize"
KERNEL_TYPE - Static variable in class edu.cmu.tetrad.util.Params
Constant KERNEL_TYPE="kernelType"
KERNEL_WIDTH - Static variable in class edu.cmu.tetrad.util.Params
Constant KERNEL_WIDTH="kernelWidth"
kernel1(double) - Method in class edu.cmu.tetrad.search.Lofs
Computes the value of the kernel function 1 for a given input.
kernel2(double) - Method in class edu.cmu.tetrad.search.Lofs
Calculates the value of the kernel2 function for the given input.
kernel3(double) - Method in class edu.cmu.tetrad.search.Lofs
This method calculates the value of the kernel function, kernel3, for a given input.
kernel4(double) - Method in class edu.cmu.tetrad.search.Lofs
Calculates the result of kernel4 function.
kernel5(double) - Method in class edu.cmu.tetrad.search.Lofs
Calculates the value of the kernel function, kernel5, for the given input.
kernel6(double) - Method in class edu.cmu.tetrad.search.Lofs
Calculates the value of the kernel function 6 given a parameter z.
kernel7(double) - Method in class edu.cmu.tetrad.search.Lofs
Computes the value of the kernel7 function for the given value.
kernel8(double) - Method in class edu.cmu.tetrad.search.Lofs
Calculates the value of the kernel8 function for the given input.
KernelGaussian - Class in edu.cmu.tetrad.search.utils
Soces the Gaussian kernel for a given bandwidth.
KernelGaussian(double) - Constructor for class edu.cmu.tetrad.search.utils.KernelGaussian
Creates a new Gaussian kernel with the given bandwidth
KernelGaussian(DataSet, Node) - Constructor for class edu.cmu.tetrad.search.utils.KernelGaussian
Creates a new Gaussian kernel using the median distance between points to set the bandwidth
KernelUtils - Class in edu.cmu.tetrad.search.utils
Provides various kernel utilities.
KMeans - Class in edu.cmu.tetrad.cluster
Implements the "batch" version of the K Means clustering algorithm-- that is, in one sweep, assign each point to its nearest center, and then in a second sweep, reset each center to the mean of the cluster for that center, repeating until convergence.
Knowledge - Class in edu.cmu.tetrad.data
Stores information about required and forbidden edges and common causes for use in algorithm.
Knowledge() - Constructor for class edu.cmu.tetrad.data.Knowledge
Constructor for Knowledge.
Knowledge(Knowledge) - Constructor for class edu.cmu.tetrad.data.Knowledge
Constructor for Knowledge.
Knowledge(Collection<String>) - Constructor for class edu.cmu.tetrad.data.Knowledge
Constructor for Knowledge.
KnowledgeEdge - Class in edu.cmu.tetrad.data
Implements a knowledge edge X-->Y as a simple ordered pair of strings.
KnowledgeEdge(String, String) - Constructor for class edu.cmu.tetrad.data.KnowledgeEdge
Constructs a knowledge edge for from-->to.
KnowledgeGroup - Class in edu.cmu.tetrad.data
Represents a "Other Group" in Knowledge, which can be understood as: Group1 -> Group2 where there are edges between all members of Group1 to Group2.
KnowledgeGroup(int) - Constructor for class edu.cmu.tetrad.data.KnowledgeGroup
Constructs an empty instance of a knowledge group.
KnowledgeGroup(int, Set<String>, Set<String>) - Constructor for class edu.cmu.tetrad.data.KnowledgeGroup
Constructs a group given the type.
KnowledgeSatisfied - Class in edu.cmu.tetrad.algcomparison.statistic
Implementation of the KnowledgeSatisfied class.
KnowledgeSatisfied() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.KnowledgeSatisfied
Constructs the statistic.
KnowledgeTransferable - Interface in edu.cmu.tetrad.data
Interface implemented by classes that are capable of participating in the transfer of knowledge objects.
Kpc - Class in edu.cmu.tetrad.search.work_in_progress
Kernelized PC algorithm.
Kpc(DataSet, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Kpc
Constructs a new PC search using for the given dataset.
kurtosis - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Score
The kurtosis.
kurtosis(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
kurtosis.
kurtosis(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
kurtosis.
kurtosis(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
kurtosis.
kurtosis(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
kurtosis.

L

LAG - Static variable in interface edu.cmu.tetrad.graph.Node
Constant LAG
LaggedEdge - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
wrapper class for passing factor+edge via a propertyChange event
LaggedEdge(String, LaggedFactor) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedEdge
Creates new LaggedEdge
LaggedFactor - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Identifies a particular factor (by name) at a particular lag (integer).
LaggedFactor(LaggedFactor) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedFactor
Copy constructor- creates a new object with the same properties as the original
LaggedFactor(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedFactor
Constructs a new lagged factor with a given name and time lag.
LagGraph - Class in edu.cmu.tetrad.graph
Implements a graph allowing nodes in the getModel time lag to have parents taken from previous time lags.
LagGraph - Interface in edu.cmu.tetrad.study.gene.tetrad.gene.history
Lag graph.
LagGraph() - Constructor for class edu.cmu.tetrad.graph.LagGraph
Constructor for LagGraph.
LagGraphParams - Class in edu.cmu.tetrad.study.gene.tetrad.gene.graph
LagGraphParams class.
LagGraphParams(Parameters) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Constructor for LagGraphParams.
LAMBDA1 - Static variable in class edu.cmu.tetrad.util.Params
Constant LAMBDA1="lambda1"
LargeScaleSimulation - Class in edu.cmu.tetrad.sem
Stores a SEM model, pared down, for purposes of simulating data sets with large numbers of variables and sample sizes.
LargeScaleSimulation(Graph) - Constructor for class edu.cmu.tetrad.sem.LargeScaleSimulation
Constructor for LargeScaleSimulation.
LargeScaleSimulation(Graph, List<Node>, int[]) - Constructor for class edu.cmu.tetrad.sem.LargeScaleSimulation
Constructor for LargeScaleSimulation.
LAST_ID - Static variable in class edu.cmu.tetrad.data.AbstractVariable
The last ID assigned to a variable.
LATENT - Enum constant in enum class edu.cmu.tetrad.graph.NodeType
Constant LATENT
LATENT_MEASURED_IMPURE_PARENTS - Static variable in class edu.cmu.tetrad.util.Params
Constant LATENT_MEASURED_IMPURE_PARENTS="latentMeasuredImpureParents"
LATENT_PREFIX - Static variable in class edu.cmu.tetrad.search.utils.ClusterUtils
The prefix for latent variables.
LatentCommonAncestorFalseNegativeBidirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
LatentCommonAncestorFalseNegativeBidirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalseNegativeBidirected
Constructor for LatentCommonAncestorFalseNegativeBidirected.
LatentCommonAncestorFalsePositiveBidirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
LatentCommonAncestorFalsePositiveBidirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalsePositiveBidirected
Constructor for LatentCommonAncestorFalsePositiveBidirected.
LatentCommonAncestorRecallBidirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
LatentCommonAncestorRecallBidirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorRecallBidirected
Constructor for LatentCommonAncestorRecallBidirected.
LatentCommonAncestorTruePositiveBidirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
LatentCommonAncestorTruePositiveBidirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorTruePositiveBidirected
Constructor for LatentCommonAncestorTruePositiveBidirected.
latentStructToEdgeListGraph(DMSearch.LatentStructure) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch.LatentStructure
latentStructToEdgeListGraph.
LatentStructure() - Constructor for class edu.cmu.tetrad.search.work_in_progress.DMSearch.LatentStructure
Constructor for LatentStructure.
layoutByCausalOrder(Graph) - Static method in class edu.cmu.tetrad.graph.LayoutUtil
layoutByCausalOrder.
LayoutUtil - Class in edu.cmu.tetrad.graph
LayoutUtil class.
LayoutUtil() - Constructor for class edu.cmu.tetrad.graph.LayoutUtil
Constructor.
LayoutUtil.FruchtermanReingoldLayout - Class in edu.cmu.tetrad.graph
Lays out a graph by linearly summing repulsive force between all nodes and attractive force between adjacent nodes.
LayoutUtil.KamadaKawaiLayout - Class in edu.cmu.tetrad.graph
Lays out a graph by placing springs between the nodes and letting the system settle (one node at a time).
LE - Enum constant in enum class edu.cmu.tetrad.sem.ParamComparison
An enum value representing the "LE" comparison type for a parameter in SEM estimation.
learn(double, int) - Method in class edu.pitt.csb.mgm.Mgm
Learn MGM traditional way with objective function tolerance.
learnBackTrack(ConvexProximal, DoubleMatrix1D, double, int) - Method in class edu.pitt.csb.mgm.ProximalGradient
learnBackTrack.
learnBNRFCI(DataSet, int, Graph) - Method in class edu.cmu.tetrad.calibration.DataForCalibrationRfci
learnBNRFCI.
learnEdges(int) - Method in class edu.pitt.csb.mgm.Mgm
Learn MGM using edge convergence using default 3 iterations of no edge changes.
learnEdges(int, int) - Method in class edu.pitt.csb.mgm.Mgm
Learn MGM using edge convergence using edgeChangeTol (see ProximalGradient for documentation).
LEE_AND_HASTIE - Static variable in class edu.cmu.tetrad.algcomparison.simulation.SimulationTypes
Constant LEE_AND_HASTIE="Mixed Lee & Hastie"
LeeHastieSimulation - Class in edu.cmu.tetrad.algcomparison.simulation
A version of the Lee and Hastic simulation which is guaranteed ot generate a discrete data set.
LeeHastieSimulation(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation
Constructor for LeeHastieSimulation.
LEFT_JUSTIFIED - Static variable in class edu.cmu.tetrad.util.TextTable
Set justification to this if the columns should be left justified.
leftRight(double[], double[]) - Method in class edu.cmu.tetrad.search.FaskOrig
A left/right judgment for double[] arrays (data) as input.
leftRightV2(double[], double[]) - Static method in class edu.cmu.tetrad.search.Fask
Calculates a left-right judgment using the difference of corrExp values between two arrays of double values.
LegalMagRet(boolean, String) - Constructor for class edu.cmu.tetrad.search.utils.GraphSearchUtils.LegalMagRet
Constructs a new LegalMagRet object.
LegalPag - Class in edu.cmu.tetrad.algcomparison.statistic
Legal PAG
LegalPag() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.LegalPag
Constructor for LegalPag.
LegalPagRet(boolean, String) - Constructor for class edu.cmu.tetrad.search.utils.GraphSearchUtils.LegalPagRet
Constructs a new LegalPagRet object.
LegalPairs - Interface in edu.cmu.tetrad.search.utils
Determines whether nodes indexed as (n1, center, n2) form a legal pair of edges in a graph for purposes of some algorithm that uses this information.
legendre(int, double) - Static method in class edu.cmu.tetrad.util.StatUtils
Computes the value of the Legendre polynomial of a given degree at a specified point x.
like() - Method in class edu.cmu.tetrad.data.BoxDataSet
Returns a dataset with the same dimensions as this dataset, but with no data.
like() - Method in class edu.cmu.tetrad.data.ByteDataBox
like.
like() - Method in interface edu.cmu.tetrad.data.DataBox
Returns a data box of the same dimensions as this one, without setting any values.
like() - Method in interface edu.cmu.tetrad.data.DataSet
Returns a dataset with the same dimensions as this dataset, but with no data.
like() - Method in class edu.cmu.tetrad.data.DoubleDataBox
like.
like() - Method in class edu.cmu.tetrad.data.FloatDataBox
like.
like() - Method in class edu.cmu.tetrad.data.IntDataBox
like.
like() - Method in class edu.cmu.tetrad.data.LongDataBox
like.
like() - Method in class edu.cmu.tetrad.data.MixedDataBox
Returns a data box of the same dimensions as this one, without setting any values.
like() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Returns a dataset with the same dimensions as this dataset, but with no data.
like() - Method in class edu.cmu.tetrad.data.ShortDataBox
like.
like() - Method in class edu.cmu.tetrad.data.VerticalDoubleDataBox
like.
like() - Method in class edu.cmu.tetrad.data.VerticalIntDataBox
like.
like() - Method in class edu.cmu.tetrad.util.Matrix
like.
like() - Method in class edu.cmu.tetrad.util.Vector
like.
like(String) - Method in class edu.cmu.tetrad.data.AbstractVariable
Creates a new node of the same type as this one with the given name.
like(String) - Method in class edu.cmu.tetrad.data.ContinuousVariable
Creates a new node of the same type as this one with the given name.
like(String) - Method in class edu.cmu.tetrad.data.DiscreteVariable
Creates a new node of the same type as this one with the given name.
like(String) - Method in class edu.cmu.tetrad.graph.GraphNode
Creates a new node of the same type as this one with the given name.
like(String) - Method in interface edu.cmu.tetrad.graph.Node
Creates a new node of the same type as this one with the given name.
LikelihoodRet() - Constructor for class edu.cmu.tetrad.bayes.BayesProperties.LikelihoodRet
Constructs a new LikelihoodRet object.
LINEAR - Enum constant in enum class edu.cmu.tetrad.search.test.Kci.KernelType
 
LINEAR_FISHER_MODEL - Static variable in class edu.cmu.tetrad.algcomparison.simulation.SimulationTypes
Constant LINEAR_FISHER_MODEL="Linear Fisher Model"
LinearFisherModel - Class in edu.cmu.tetrad.algcomparison.simulation
Linear Fisher Model.
LinearFisherModel(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
Constructor for LinearFisherModel.
LinearFisherModel(RandomGraph, List<DataModel>) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel
Constructor for LinearFisherModel.
LinearFunction - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Implements a linear update function, Gi.0 = L(Parents(G0.0)) + ei, where P is a polynomial function and ei is a random noise term.
LinearFunction(LagGraph) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Constructs a polyomial function where each factor is given a zero polynomial.
LinearGaussian - Annotation Interface in edu.cmu.tetrad.annotation
Data with Gaussian variables that have linear relationships.
LinearSimExp1 - Class in edu.cmu.tetrad.study.gene.tetrad.gene.simexp
Implements a particular simulation for experimental purposes.
LinearSimExp1(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.simexp.LinearSimExp1
Constructor for LinearSimExp1.
LinearSineSimulation - Class in edu.cmu.tetrad.algcomparison.simulation
A simulation method based on the mixed variable polynomial assumption.
LinearSineSimulation(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Constructor for LinearSineSimulation.
LingamStudy - Class in edu.cmu.tetrad.study.examples.conditions
An example script to simulate data and run a comparison analysis on it.
listColliderTriples(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Generates a list of triples where a node acts as a collider in a given graph.
listDiscriminatingPaths(Graph, int, boolean) - Static method in class edu.cmu.tetrad.search.utils.FciOrient
Lists all the discriminating paths in the given graph.
listDiscriminatingPaths(Graph, Node, Node, int, boolean) - Static method in class edu.cmu.tetrad.search.utils.FciOrient
Lists the discriminating paths for <w, y> in the graph.
listUnmeasuredLatents() - Method in interface edu.cmu.tetrad.sem.ISemIm
listUnmeasuredLatents.
listUnmeasuredLatents() - Method in class edu.cmu.tetrad.sem.SemIm
listUnmeasuredLatents.
lngamma(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
This is a more literal (that is, exact) copy of the log gamma method from Numerical Recipes than the following one.
loadContinuousData(File, String, char, String, boolean, Delimiter, boolean) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
Loads a continuous dataset from a file.
LoadContinuousDataAndGraphs - Class in edu.cmu.tetrad.data.simulation
Load data sets and graphs from a directory.
LoadContinuousDataAndGraphs(String) - Constructor for class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs
Constructor for LoadContinuousDataAndGraphs.
LoadContinuousDataAndSingleGraph - Class in edu.cmu.tetrad.data.simulation
Load data sets and graphs from a directory.
LoadContinuousDataAndSingleGraph(String) - Constructor for class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph
Constructor for LoadContinuousDataAndSingleGraph.
LoadContinuousDataSmithSim - Class in edu.cmu.tetrad.data.simulation
Load data sets and graphs from a directory.
LoadContinuousDataSmithSim(String) - Constructor for class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
Constructor for LoadContinuousDataSmithSim.
loadCovarianceMatrix(char[], String, DelimiterType, char, String) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
Parses a covariance matrix from a char[] array.
loadCovarianceMatrix(File, String, DelimiterType, char, String) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
Parses the given files for a tabular data set, returning a RectangularDataSet if successful.
loadData(String, String) - Static method in class edu.pitt.csb.mgm.MixedUtils
loadData.
LoadDataAndGraphs - Class in edu.cmu.tetrad.data.simulation
Load data sets and graphs from a directory.
LoadDataAndGraphs(String) - Constructor for class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs
Constructor for LoadDataAndGraphs.
LoadDataFromFileWithoutGraph - Class in edu.cmu.tetrad.data.simulation
Load data sets and graphs from a directory.
LoadDataFromFileWithoutGraph(String) - Constructor for class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
Constructor for LoadDataFromFileWithoutGraph.
loadDataSet(String, String) - Static method in class edu.pitt.csb.mgm.MixedUtils
loadDataSet.
loadDelim(String, String) - Static method in class edu.pitt.csb.mgm.MixedUtils
loadDelim.
loadDiscreteData(File, String, char, String, boolean, Delimiter, boolean) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
Loads a discrete dataset from a file.
LOADED_FROM_FILES - Static variable in class edu.cmu.tetrad.algcomparison.simulation.SimulationTypes
Constant LOADED_FROM_FILES="Loaded From Files"
loadGraph(File) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
loadGraph.
loadGraphAmatCpdag(File) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
Loads a CPDAG in the "amat.cpdag" format of PCALG.
loadGraphAmatPag(File) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
Loads a PAG in the "amat.pag" format of PCALG.
loadGraphBNTPcMatrix(List<Node>, DataSet) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
loadGraphBNTPcMatrix.
loadGraphJson(File) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
loadGraphJson.
loadGraphRMatrix(Graph) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
loadGraphRMatrix.
loadGraphRuben(File) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
loadGraphRuben.
loadGraphTxt(Graph, boolean) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
Converts a given graph to human-readable text format.
loadGraphTxt(File) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
loadGraphTxt.
loadKnowledge(File, DelimiterType, String) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
Loads knowledge from a file.
loadMixedData(File, String, char, String, boolean, int, Delimiter, boolean) - Static method in class edu.cmu.tetrad.data.SimpleDataLoader
Loads a mixed dataset from a file.
loadRSpecial(File) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
loadRSpecial.
LOCAL_MARKOV - Enum constant in enum class edu.cmu.tetrad.search.ConditioningSetType
Testing independence facts implied by the graph, conditioning on the parents of each variable in the graph.
LocalGraphConfusion - Class in edu.cmu.tetrad.algcomparison.statistic.utils
A confusion matrix for local graph accuracy check --i.e.
LocalGraphConfusion(Graph, Graph) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.utils.LocalGraphConfusion
Constructs a new LocalGraphConfusion object from the given graphs.
LocalGraphPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The LocalGraphPrecision class implements the Statistic interface and represents the Local Graph Precision statistic.
LocalGraphPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.LocalGraphPrecision
The default constructor of the LocalGraphPrecision class.
LocalGraphRecall - Class in edu.cmu.tetrad.algcomparison.statistic
LocalGraphRecall implements the Statistic interface and represents the local graph recall statistic.
LocalGraphRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.LocalGraphRecall
The default constructor of the LocalGraphRecall class.
localMarkovAdjustPValues(Graph, boolean, IndependenceTest, Map<Pair<Node, Node>, Set<Double>>, Pair<Node, Node>) - Static method in class edu.cmu.tetrad.search.utils.EnsureMarkov
Adjusts the p-values for a local Markov condition in a given constraint-based partially directed acyclic graph (CPDAG).
localMarkovInitializePValues(Graph, boolean, IndependenceTest, Map<Pair<Node, Node>, Set<Double>>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Initializes and evaluates p-values for local Markov properties in a given graph.
localScore() - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
localScore.
localScore(int) - Method in class edu.cmu.tetrad.search.score.GraphScore
Returns the local score of the gien node in the graph.
localScore(int) - Method in class edu.cmu.tetrad.search.score.ImagesScore
Returns the local score of the gien node in the graph.
localScore(int) - Method in class edu.cmu.tetrad.search.score.IndTestScore
Returns the local score of the gien node in the graph.
localScore(int) - Method in interface edu.cmu.tetrad.search.score.Score
Returns the local score of the gien node in the graph.
localScore(int[]) - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
localScore.
localScore(int, int) - Method in class edu.cmu.tetrad.search.score.GraphScore
localScore.
localScore(int, int) - Method in class edu.cmu.tetrad.search.score.ImagesScore
Returns the (aggregate) local score for a variable given one of its parents, which is obtained by averaging the local such scores obtained from each individual score provided in the constructor, excluding scores that are returned as undefined (which are left out of the average).
localScore(int, int) - Method in class edu.cmu.tetrad.search.score.IndTestScore
localScore.
localScore(int, int) - Method in interface edu.cmu.tetrad.search.score.Score
Returns the local score of the graph.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.score.BasisFunctionBicScore
Calculates the local score for a given node and its parent nodes.
localScore(int, int[]) - Method in class edu.cmu.tetrad.search.score.BdeScore
Returns the score for the given parent given its parents, where these are specified as column indices into the dataset.
localScore(int, int[]) - Method in class edu.cmu.tetrad.search.score.BdeuScore
Calculates the local score of a node given its parents.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianScore
Calculates the sample likelihood and BIC score for index i given its parents in a simple SEM model.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.score.DegenerateGaussianScore
Calculates the sample likelihood and BIC score for i given its parents in a simple SEM model.
localScore(int, int[]) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
The score of a node given its parents.
localScore(int, int[]) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
The score of a node given its parents.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.score.EbicScore
Returns the score of the node at index i, given its parents.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.score.GicScores
Calculates the sample likelihood and BIC score for index i given its parents in a simple SEM model.
localScore(int, int[]) - Method in class edu.cmu.tetrad.search.score.GraphScore
Calculates the sample likelihood and BIC score for y given its z in a simple SEM model.
localScore(int, int[]) - Method in class edu.cmu.tetrad.search.score.ImagesScore
Returns the (aggregate) local score for a variable given its parents, which is obtained by averaging the local such scores obtained from each individual score provided in the constructor, excluding scores that are returned as undefined (which are left out of the average).
localScore(int, int[]) - Method in class edu.cmu.tetrad.search.score.IndTestScore
Calculates the sample likelihood and BIC score for i, given its parents in a simple SEM model
localScore(int, int...) - Method in class edu.cmu.tetrad.search.score.MvpScore
The local score of the child given its parents.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.score.PoissonPriorScore
Returns the score of the node at index i, given its parents.
localScore(int, int...) - Method in interface edu.cmu.tetrad.search.score.Score
The score of a node given its parents.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the score for the given node and its parents.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.score.ZsbScore
Returns the score for the child given the parents.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
The score of a node given its parents.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
The score of a node given its parents.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
The score of a node given its parents.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.work_in_progress.MnlrScore
The local score of the child given its parents.
localScore(int, int...) - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Calculates the sample likelihood and BIC score for i given its parents in a simple SEM model
localScore(int, int[], int) - Method in class edu.cmu.tetrad.search.score.ImagesScore
Returns the (aggregate) local score for a variable given its parents, which is obtained by averaging the local such scores obtained from each individual score provided in the constructor, excluding scores that are returned as undefined (which are left out of the average).
localScore(int, int[], int[], int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
 
localScore(int, int[], int[], int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Calculates the local score for a given node considering its parents.
localScore(int, int[], int[], int[]) - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Calculates the local score for a given node in the context of its parent nodes and children population.
localScore1(int, int[], int[], int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Computes the local score for a given node considering both population and context-specific parents.
localScore1(int, int[], int[], int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Computes a local score based on the given node, its parents, and its children's populations.
localScore1(int, int[], int[], int[]) - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Calculates the local score for a given node in the context of its parent nodes and children population, without using structure prior.
localScoreDiff(int, int) - Method in class edu.cmu.tetrad.search.score.GraphScore
Returns the local score difference of the graph.
localScoreDiff(int, int) - Method in interface edu.cmu.tetrad.search.score.Score
Returns the local score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.BasisFunctionBicScore
 
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.BdeScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.BdeuScore
Calculates the difference in local scores between two nodes y and x, when x is added to a set of nodes z.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianScore
Calculates localScore(y | z, x) - localScore(z).
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.DegenerateGaussianScore
Calculates localScore(y | z, x) - localScore(z).
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.EbicScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.GicScores
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.GraphScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.ImagesScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.IndTestScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.MvpScore
Returns localScore(y | z, x) - localScore(y | z).
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.PoissonPriorScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in interface edu.cmu.tetrad.search.score.Score
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.ZsbScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Returns the score difference of the graph.
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.MnlrScore
localScore(y | z, x) - localScore(y | z).
localScoreDiff(int, int, int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Returns the score difference of the graph.
localScoreDiff(int, int, int[], int[], int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Computes the difference in local scores when element x is appended to the array z.
localScoreDiff(int, int, int[], int[], int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Calculates the difference in local scores for a given variable when it is added to or removed from a set of parent variables.
localScoreDiff(int, int, int[], int[], int[]) - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Calculates the difference between local scores before and after introducing a change in the relationship between nodes x and y, considering their parent and children populations.
LOCK - Enum constant in enum class edu.cmu.tetrad.graph.NodeType
Constant LOCK
Lofs - Class in edu.cmu.tetrad.search
Implements a number of methods which take a fixed graph as input and use linear, non-Gaussian methods to orient the edges in the graph.
Lofs(Graph, List<DataSet>) - Constructor for class edu.cmu.tetrad.search.Lofs
Constructor.
Lofs.Rule - Enum Class in edu.cmu.tetrad.search
Give a list of options for rules for doing the non-Gaussian orientations.
Lofs.Score - Enum Class in edu.cmu.tetrad.search
Gives a list of options for non-Gaussian transformations that can be used for some scores.
log(String) - Method in class edu.cmu.tetrad.util.TetradLogger
Logs the given message regardless of the logger's getModel settings.
logbeta(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
Calculates the log beta function of p and q.
logChoose(int, int) - Static method in class edu.cmu.tetrad.util.MathUtils
logChoose.
logClusters(Set<Set<Integer>>, List<Node>) - Static method in class edu.cmu.tetrad.search.utils.ClusterUtils
Logs the clusters.
logCombinations(int, int) - Static method in class edu.cmu.tetrad.util.ChoiceGenerator
Returns the natural logarithm of the number of combinations of a choose b.
logcosh - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Score
The logcosh.
LOGCOSH - Static variable in class edu.cmu.tetrad.search.FastIca
One of the function types that can be used to approximate negative entropy.
logCoshExp() - Static method in class edu.cmu.tetrad.util.StatUtils
logCoshExp.
logCoshScore(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
logCoshScore.
logData(DataSet, double, boolean, int) - Static method in class edu.cmu.tetrad.data.DataTransforms
Log or unlog data
logDataModelList(String, DataModelList) - Static method in class edu.cmu.tetrad.data.LogDataUtils
logDataModelList.
LogDataUtils - Class in edu.cmu.tetrad.data
Sundry methods for logging data.
logFactorial(int) - Static method in class edu.cmu.tetrad.util.MathUtils
logFactorial.
logistic(double) - Static method in class edu.cmu.tetrad.util.MathUtils
logistic.
LogisticRegression - Class in edu.cmu.tetrad.regression
Implements a logistic regression algorithm based on a Javascript implementation by John Pezzullo.
LogisticRegression(DataSet) - Constructor for class edu.cmu.tetrad.regression.LogisticRegression
A mixed data set.
LogisticRegression.Result - Class in edu.cmu.tetrad.regression
The result of a logistic regression.
LogNormal - Class in edu.cmu.tetrad.util.dist
Represents a lognormal distribution for purposes of sampling.
LogNormal(double) - Constructor for class edu.cmu.tetrad.util.dist.LogNormal
Constructor for LogNormal.
logsum(List<Double>) - Static method in class edu.cmu.tetrad.util.StatUtils
logsum.
LogUtils - Class in edu.cmu.tetrad.util
Sets up streams for logging via the Java logging API.
LogUtilsSearch - Class in edu.cmu.tetrad.search.utils
Contains utilities for logging search steps.
LogUtilsSearch() - Constructor for class edu.cmu.tetrad.search.utils.LogUtilsSearch
Constructor.
LongDataBox - Class in edu.cmu.tetrad.data
Stores a 2D array of long data.
LongDataBox(long[][]) - Constructor for class edu.cmu.tetrad.data.LongDataBox
Constructs a new data box using the given 2D long data array as data.
LOWER_BOUND - Static variable in class edu.cmu.tetrad.util.Params
Constant LOWER_BOUND="lowerBound"
LPAREN - Enum constant in enum class edu.cmu.tetrad.calculator.parser.Token
Left parenthesis.
LT - Enum constant in enum class edu.cmu.tetrad.sem.ParamComparison
Represents the "LT" comparison type for a parameter in SEM estimation.
LT - Enum constant in enum class edu.cmu.tetrad.sem.ParamConstraintType
Represents a parameter constraint type LT (less than).
LTestBoolSearch - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu
This is merely a main program used to read a binarized measurement data set and to instantiate a BoolSearch and run one or more search methods of that instance.
LTestBoolSearch - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
This is merely a main program used to read a binarized measurement data set and to instantiate a BoolSearch and run one or more search methods of that instance.
LTester - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua
Class that makes some very simple tests on the classes LtMatrix, Graph, and Biolingua
LTestPredictorSearch - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker
LTestPredictorSearch class.
LTestQnet3 - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu
LTestQnet3 class.
LTestReveal - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
LTestReveal class.
LTestRevealSearch - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal
This is merely a main program used to read a binarized measurement data set and to instantiate a RevealSearch and run one or more search methods of that instance.
LTestRevealSearch - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
This is merely a main program used to read a binarized measurement data set and to instantiate a RevealSearch and run one or more search methods of that instance.
LTestSsys1 - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu
LTestSsys1 class.
LTMatrix - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util
Implements a space-efficient Lower Triangular Matrix of elements of type short
LTMatrix(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrix
Creates a lower triangular matrix reading it from file fname.
LTMatrix(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrix
Creates a lower triangular matrix with nrows rows.
LTMatrixF - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util
Implements a space-efficient Lower Triangular Matrix of elements of type float
LTMatrixF(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrixF
Creates a lower triangular matrix reading it from file fname.
LTMatrixF(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrixF
Creates a lower triangular matrix with nrows rows.
LV_LITE_STARTS_WITH - Static variable in class edu.cmu.tetrad.util.Params
Constant LV_LITE_STARTS_WITGH="LvLiteStartsWith"
LvDumb - Class in edu.cmu.tetrad.search
LV-Dumb is a class that implements the IGraphSearch interface.
LvDumb(Score) - Constructor for class edu.cmu.tetrad.search.LvDumb
LV-Lite constructor.
LvLite - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
This class represents the LV-Lite algorithm, which is an implementation of the GFCI algorithm for learning causal structures from observational data using the BOSS algorithm as an initial CPDAG and using all score-based steps afterward.
LvLite - Class in edu.cmu.tetrad.search
The LV-Lite algorithm (Latent Variable "Lite") algorithm implements a search algorithm for learning the structure of a graphical model from observational data with latent variables.
LvLite() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
This class represents a LV-Lite algorithm.
LvLite(IndependenceWrapper, ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
LV-Lite is a class that represents a LV-Lite algorithm.
LvLite(Graph, IndependenceTest) - Constructor for class edu.cmu.tetrad.search.LvLite
Alternative LV-Lite constructor.
LvLite(IndependenceTest, Score) - Constructor for class edu.cmu.tetrad.search.LvLite
LV-Lite constructor.
LvLite.ExtraEdgeRemovalStyle - Enum Class in edu.cmu.tetrad.search
The ExtraEdgeRemovalStyle enum specifies the styles for removing extra edges.
LvLite.START_WITH - Enum Class in edu.cmu.tetrad.search
Enumeration representing different start options.

M

MagCgBicScore - Class in edu.cmu.tetrad.search.work_in_progress
Gives a BIC score for a linear, Gaussian MAG (Mixed Ancestral Graph).
MagCgBicScore(DataSet) - Constructor for class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Constructor.
MagCgBicScore(DataSet, boolean) - Constructor for class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Constructor.
MagCgScore - Class in edu.cmu.tetrad.algcomparison.statistic
Takes a MAG in a PAG using Zhang's method and then reports the MAG DG BIC score for it.
MagCgScore() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MagCgScore
Constructs the statistic.
MagDgBicScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for degenerate Gaussian BIC score
MagDgBicScore - Class in edu.cmu.tetrad.search.work_in_progress
Gives a BIC score for a linear, Gaussian MAG (Mixed Ancestral Graph).
MagDgBicScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.MagDgBicScore
Initializes a new instance of the DegenerateGaussianBicScore class.
MagDgBicScore(DataSet) - Constructor for class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Constructor.
MagDgBicScore(DataSet, boolean) - Constructor for class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Constructor.
MagDgScore - Class in edu.cmu.tetrad.algcomparison.statistic
Takes a MAG in a PAG using Zhang's method and then reports the MAG DG BIC score for it.
MagDgScore() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MagDgScore
Constructs the statistic.
magFromPag(Graph) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Picks a random Maximal Ancestral Graph (MAG) from the given Partial Ancestral Graph (PAG) by randomly orienting the circle endpoints as either tail or arrow and then applying the final FCI orient algorithm after each change.
MagSemBicScore - Class in edu.cmu.tetrad.search.work_in_progress
Gives a BIC score for a linear, Gaussian MAG (Mixed Ancestral Graph).
MagSemBicScore(DataSet, boolean) - Constructor for class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Constructor.
MagSemBicScore(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Constructor.
MagSemBicTest - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Fisher Z test.
MagSemBicTest() - Constructor for class edu.cmu.tetrad.algcomparison.independence.MagSemBicTest
Constructs a new instance of the test.
MagSemScore - Class in edu.cmu.tetrad.algcomparison.statistic
Takes a MAG in a PAG using Zhang's method and then reports the MAG SEM BIC score for it.
MagSemScore() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MagSemScore
Constructs the statistic.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.ExampleCompareFromFiles
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.ExampleCompareSimulation
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.ExampleCompareSimulation2
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.ExampleCompareSimulationTimeSeries
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.ExampleNonlinearSave
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.ExampleSave
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.MVPCompareFromFiles
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.RunConfig
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.RunKemmeren
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.Save
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.SaveDGSimulations
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.TestBoss
main.
main(String...) - Static method in class edu.cmu.tetrad.algcomparison.examples.TestDegenerateGaussian
The main method initializes various parameters, statistics, algorithms, simulations, and a comparison object.
main(String[]) - Static method in class edu.cmu.tetrad.calibration.DataForCalibrationRfci
main.
main(String[]) - Static method in class edu.cmu.tetrad.classify.ClassifierMbDiscrete
Runs MbClassify using moves-line arguments.
main(String[]) - Static method in class edu.cmu.tetrad.data.GeneralAndersonDarlingTest
main.
main(String[]) - Static method in class edu.cmu.tetrad.graph.Paths.AllCliquesAlgorithm
Main method.
main(String[]) - Static method in class edu.cmu.tetrad.search.FciOrientDijkstra
A simple test of the Dijkstra algorithm.
main(String...) - Static method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
The main methods.
main(String[]) - Static method in class edu.cmu.tetrad.search.utils.HungarianAlgorithm
main.
main(String[]) - Static method in class edu.cmu.tetrad.search.utils.R5R9Dijkstra
A simple test of the Dijkstra algorithm.
main(String...) - Static method in class edu.cmu.tetrad.search.work_in_progress.DemixerMMLKun
main.
main(String...) - Static method in class edu.cmu.tetrad.simulation.GdistanceApply
main.
main(String...) - Static method in class edu.cmu.tetrad.simulation.GdistanceRandomApply
main.
main(String...) - Static method in class edu.cmu.tetrad.simulation.GdistanceTest
The main method generates random graphs, loads a location map, calculates the distance between two graphs, and saves the output to a file.
main(String...) - Static method in class edu.cmu.tetrad.simulation.HsimCompareRepeat
main.
main(String[]) - Static method in class edu.cmu.tetrad.simulation.HsimEvalFromData
main.
main(String[]) - Static method in class edu.cmu.tetrad.simulation.HsimRepeatAuto
main.
main(String[]) - Static method in class edu.cmu.tetrad.simulation.HsimSchedule
main.
main(String[]) - Static method in class edu.cmu.tetrad.simulation.HsimStudy
main.
main(String[]) - Static method in class edu.cmu.tetrad.simulation.HsimStudyAuto
main.
main(String...) - Static method in class edu.cmu.tetrad.study.examples.conditions.BryanSensitivityStudy
Run the example.
main(String...) - Static method in class edu.cmu.tetrad.study.examples.conditions.ExampleCompareFromFiles
main.
main(String...) - Static method in class edu.cmu.tetrad.study.examples.conditions.ExampleCompareSimulation
main.
main(String...) - Static method in class edu.cmu.tetrad.study.examples.conditions.ExampleCompareSimulationDiscrete
main.
main(String...) - Static method in class edu.cmu.tetrad.study.examples.conditions.ExampleFirstInflection
main.
main(String...) - Static method in class edu.cmu.tetrad.study.examples.conditions.ExampleSave
main.
main(String...) - Static method in class edu.cmu.tetrad.study.examples.conditions.ExampleStars
main.
main(String...) - Static method in class edu.cmu.tetrad.study.examples.conditions.LingamStudy
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.LTestBoolSearch
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.LTestQnet3
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.LTestSsys1
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.BiolinguaRunner
Main method, runs the Biolingua algorithm
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.LTester
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.LTestPredictorSearch
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ReadControl
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ReadIdeker
The main method processes input data and performs various calculations and predictions.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.LTestRevealSearch
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.LTestBoolSearch
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.LTestReveal
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.LTestRevealSearch
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.SimulateNetwork
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.SimulateNetworkMain
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.simexp.LinearSimExp1
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.util.HandleyConvert
Converts the graph file from the moves line.
main(String...) - Static method in class edu.cmu.tetrad.study.performance.ComparisonScript
main.
main(String...) - Static method in class edu.cmu.tetrad.study.performance.ExploreComparison
main.
main(String...) - Static method in class edu.cmu.tetrad.study.performance.PerformanceTests
main.
main(String...) - Static method in class edu.cmu.tetrad.study.performance.PerformanceTestsDan
main.
main(String[]) - Static method in class edu.cmu.tetrad.study.RBExperiments
Main method for executing the RBExperiments class and running a series of experiments.
main(String[]) - Static method in class edu.cmu.tetrad.util.RandomUtil
main.
main(String[]) - Static method in class edu.cmu.tetrad.util.UniformityTest
The main method of the UniformityTest class.
main(String[]) - Static method in class edu.pitt.csb.mgm.ExampleMixedSearch
main.
main(String[]) - Static method in class edu.pitt.csb.mgm.ExploreIndepTests
main.
main(String[]) - Static method in class edu.pitt.csb.mgm.Mgm
main.
main(String[]) - Static method in class edu.pitt.csb.mgm.MixedUtils
main.
main(String[]) - Static method in class edu.pitt.csb.stability.StabilityUtils
main.
main(String[]) - Static method in class edu.pitt.dbmi.algo.bayesian.constraint.inference.BayesianConstraintInference
Main method.
main(String[]) - Static method in class edu.pitt.dbmi.algo.bayesian.constraint.inference.BayesianConstraintInferenceTest
Main method.
main(String[]) - Static method in class edu.pitt.isp.sverchkov.data.AdTreeTest
Test the AD tree
majority - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Majority method
majority - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
The majority method.
Majority - Enum constant in enum class edu.pitt.dbmi.algo.resampling.ResamplingEdgeEnsemble
Choose an edge iff its prob.
makeBayesIm(String) - Static method in class edu.cmu.tetrad.bayes.BayesBifParser
Parses a string in BayesBif format and converts it into a BayesIm object.
makeContinuousData(DataSet) - Static method in class edu.pitt.csb.mgm.MixedUtils
makeContinuousData.
makeDAG(int, double, int) - Method in class edu.cmu.tetrad.calibration.DataForCalibrationRfci
makeDAG.
makeGraph(Matrix, List<Node>) - Static method in class edu.cmu.tetrad.search.IcaLingD
Returns a graph given a coefficient matrix and a list of variables.
makeGraph(List<Cstar.Record>) - Method in class edu.cmu.tetrad.search.Cstar
Makes a graph of the estimated predictors to the effect.
makeLatexTable(String[][]) - Static method in class edu.cmu.tetrad.simulation.HsimUtils
makeLatexTable.
makeMixedData(DataSet, Map<String, Integer>) - Static method in class edu.pitt.csb.mgm.MixedUtils
makeMixedData.
makeMixedData(DataSet, Map<String, String>, int) - Static method in class edu.pitt.csb.mgm.MixedUtils
makeMixedData.
makeMixedGraph(Graph, Map<String, Integer>) - Static method in class edu.pitt.csb.mgm.MixedUtils
makeMixedGraph.
makeTable(LinkedList<Cstar.Record>) - Method in class edu.cmu.tetrad.search.Cstar
Returns a text table from the given records
makeValidOrder(List<Node>) - Method in class edu.cmu.tetrad.graph.Paths
Reorders the given order into a valid causal order for either a DAG or a CPDAG.
makeVertIntBox(DataSet) - Static method in class edu.cmu.tetrad.simulation.HsimUtils
makeVertIntBox.
ManipulatingBayesUpdater - Interface in edu.cmu.tetrad.bayes
Interface for a Bayes updating algorithm that's capable of doing manipulation.
Manipulation - Class in edu.cmu.tetrad.bayes
Stores information for a variable source about evidence we have for each variable as well as whether each variable has been manipulated.
Manipulation(Manipulation) - Constructor for class edu.cmu.tetrad.bayes.Manipulation
Copy constructor.
Manipulation(VariableSource) - Constructor for class edu.cmu.tetrad.bayes.Manipulation
Constructs a container for evidence for the given Bayes IM.
MANUAL - Enum constant in enum class edu.cmu.tetrad.bayes.MlBayesIm.InitializationMethod
Represents a manual initialization method.
MANUAL - Enum constant in enum class edu.cmu.tetrad.search.score.GicScores.RuleType
The lambda is set manually.
ManualLagGraph - Class in edu.cmu.tetrad.study.gene.tetrad.gene.graph
Constructs as a (manual) update graph.
ManualLagGraph(ManualLagGraphParams) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Using the given parameters, constructs an BasicLagGraph.
ManualLagGraphParams - Class in edu.cmu.tetrad.study.gene.tetrad.gene.graph
Stores the parameters needed to generate a new lag graph, whether randomized or manually constructed.
ManualLagGraphParams() - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraphParams
Constructs a new parameters object.
Mapping - Class in edu.cmu.tetrad.sem
Maps a parameter to the matrix element where its value is stored in the model.
Mapping(ISemIm, Parameter, Matrix, int, int) - Constructor for class edu.cmu.tetrad.sem.Mapping
Constructs matrix new mapping using the given freeParameters.
MARKOV_BLANKET - Enum constant in enum class edu.cmu.tetrad.search.ConditioningSetType
Conditioning on the Markov blanket of each variable in the graph.
markovBlanket(Node) - Method in class edu.cmu.tetrad.graph.Paths
Returns the Markov Blanket of a given node in the graph.
markovBlanket(Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns a Markov blanket of a node for a DAG, CPDAG, MAG, or PAG.
markovBlanketSubgraph(Node, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Calculates the subgraph over the Markov blanket of a target node in a given DAG, CPDAG, MAG, or PAG.
MarkovCheck - Class in edu.cmu.tetrad.search
Checks whether a graph is Markov given a data set.
MarkovCheck(Graph, IndependenceTest, ConditioningSetType) - Constructor for class edu.cmu.tetrad.search.MarkovCheck
Constructor.
MarkovCheck.AllSubsetsIndependenceFacts - Class in edu.cmu.tetrad.search
Stores the set of m-separation facts and the set of m-connection facts for a graph, for the global check.
MarkovCheck.MarkovCheckRecord - Record Class in edu.cmu.tetrad.search
A single record for the results of the Markov check.
MarkovCheckAdPasses - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckAdPasses() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPasses
Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckAdPassesBestOf10 - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckAdPassesBestOf10() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPassesBestOf10
Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckAndersonDarlingP - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckAndersonDarlingP() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingP
Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckAndersonDarlingPBestOf10 - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckAndersonDarlingPBestOf10() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingPBestOf10
Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckBinomialP - Class in edu.cmu.tetrad.algcomparison.statistic
Represents a markov check statistic that calculates the Binomial P value for whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckBinomialP() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialP
Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckBinomialPBestOf10 - Class in edu.cmu.tetrad.algcomparison.statistic
Represents a markov check statistic that calculates the Binomial P value for whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckBinomialPBestOf10() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialPBestOf10
Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckKolmogorovSmirnoffP - Class in edu.cmu.tetrad.algcomparison.statistic
Represents a markov check statistic that calculates the Kolmogorov-Smirnoff P value for whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckKolmogorovSmirnoffP() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffP
Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckKolmogorovSmirnoffPBestOf10 - Class in edu.cmu.tetrad.algcomparison.statistic
Represents a markov check statistic that calculates the Kolmogorov-Smirnoff P value for whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckKolmogorovSmirnoffPBestOf10() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffPBestOf10
Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckKsPasses - Class in edu.cmu.tetrad.algcomparison.statistic
Represents a markov check statistic that calculates the Kolmogorov-Smirnoff P value for whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckKsPasses() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPasses
Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckKsPassesBestOf10 - Class in edu.cmu.tetrad.algcomparison.statistic
Represents a markov check statistic that calculates the Kolmogorov-Smirnoff P value for whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckKsPassesBestOf10() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPassesBestOf10
Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
MarkovCheckRecord(double, double, double, double, double, double, int, int) - Constructor for record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Creates an instance of a MarkovCheckRecord record class.
markovIndependence(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.EnsureMarkov
Checks the independence of two nodes given a set of conditioning nodes, and if Markov is to be preserved, checks to make sure the additional independence does not generate p-values that violate the Markov property.
MathewsCorrAdj - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the Matthew's correlation coefficient for adjacencies.
MathewsCorrAdj() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrAdj
Constructs a new instance of the statistic.
MathewsCorrArrow - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the Matthew's correlation coefficient for adjacencies.
MathewsCorrArrow() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrArrow
Constructs a new instance of the statistic.
MathUtils - Class in edu.cmu.tetrad.util
Some extra mathematical functions not contained in org.apache.commons.math3.util.FastMath.
Matrix - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util
Implements a Matrix of elements of type short
Matrix - Class in edu.cmu.tetrad.util
Wraps the Apache math3 linear algebra library for most uses in Tetrad.
Matrix(double[][]) - Constructor for class edu.cmu.tetrad.util.Matrix
Constructor for Matrix.
Matrix(int, int) - Constructor for class edu.cmu.tetrad.util.Matrix
Constructor for Matrix.
Matrix(Matrix) - Constructor for class edu.cmu.tetrad.util.Matrix
Constructor for Matrix.
Matrix(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.Matrix
Creates a matrix reading it from a file fname.
Matrix(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.Matrix
Creates a matrix with name mname, and nrows rows.
Matrix(RealMatrix) - Constructor for class edu.cmu.tetrad.util.Matrix
Constructor for Matrix.
MatrixF - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util
Implements a Matrix of elements of type float
MatrixF(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.MatrixF
Creates a matrix reading it from a file fname.
MatrixF(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.MatrixF
Creates a matrix with name mname, and nrows rows.
MatrixUtils - Class in edu.cmu.tetrad.util
Class Matrix includes several public static functions performing matrix operations.
max(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
max.
max(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
max.
max(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
max.
max(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
max.
MAX - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Constant MAX=1
MAX - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.history.SimpleRandomizer
Indicates maximum indegree.
MAX_BLOCKING_PATH_LENGTH - Static variable in class edu.cmu.tetrad.util.Params
Constant MAX_BLOCKING_PATH_LENGTH="maxBlockingPathLength"
MAX_CATEGORIES - Static variable in class edu.cmu.tetrad.util.Params
Constant MAX_CATEGORIES="maxCategories"
MAX_DEGREE - Static variable in class edu.cmu.tetrad.util.Params
Constant MAX_DEGREE="maxDegree"
MAX_DISCRIMINATING_PATH_LENGTH - Static variable in class edu.cmu.tetrad.util.Params
Constant MAX_PATH_LENGTH="maxPathLength"
MAX_DISTINCT_VALUES_DISCRETE - Static variable in class edu.cmu.tetrad.util.Params
Constant MAX_DISTINCT_VALUES_DISCRETE="maxDistinctValuesDiscrete"
MAX_FLOAT - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Maximum float value
MAX_INDEGREE - Static variable in class edu.cmu.tetrad.util.Params
Constant MAX_INDEGREE="maxIndegree"
MAX_INT - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Maximum int value
MAX_ITERATIONS - Static variable in class edu.cmu.tetrad.util.Params
Constant MAX_ITERATIONS="maxIterations"
MAX_OUTDEGREE - Static variable in class edu.cmu.tetrad.util.Params
Constant MAX_OUTDEGREE="maxOutdegree"
MAX_P - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.ColliderDiscovery
FAS with Max P reasoning.
MAX_SCORE_DROP - Static variable in class edu.cmu.tetrad.util.Params
Constant MAX_SCORE_DROP="maxScoreDrop"
MAX_SEPSET_SIZE - Static variable in class edu.cmu.tetrad.util.Params
Constant MAX_SEPSET_SIZE="maxSepsetSize"
MAX_SHORT - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Maximum short value
maxCliques() - Method in class edu.cmu.tetrad.graph.Paths
Returns a set of all maximum cliques in the graph.
maxEntApprox(double[]) - Static method in class edu.cmu.tetrad.search.DirectLingam
Calculates the maximum entropy approximation for the given array of values.
maxEntApprox(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
maxEntApprox.
Maximal - Class in edu.cmu.tetrad.algcomparison.statistic
Checks whether a PAG is maximal.
Maximal() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.Maximal
Constructor for LegalPag.
maximalCliques(Graph, List<Node>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Finds all maximal cliques in a given graph.
MaximalityCondition - Class in edu.cmu.tetrad.algcomparison.statistic
MaximalMag statistic.
MaximalityCondition() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.MaximalityCondition
Constructs a new instance of the statistic.
maximization(double) - Method in class edu.cmu.tetrad.bayes.EmBayesEstimator
This method iteratively estimates the parameters of the Bayes net using the dataset until the parameters don't change.
maximization(double) - Method in class edu.cmu.tetrad.bayes.FactoredBayesStructuralEM
This method allows specification of the tolerance parameter used in Bayes EM estimation.
maximizeDiagonal(Matrix) - Static method in class edu.cmu.tetrad.search.IcaLingD
Finds a column permutation of the W matrix that maximizes the sum of 1 / |Wii| for diagonal elements Wii in W.
MAXIT - Static variable in class edu.cmu.tetrad.util.Params
Constant MAXIT="maxit"
MaxP - Class in edu.cmu.tetrad.search.utils
Performs a Max-P orientation of unshielded triples in a graph.
MaxP(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.utils.MaxP
Constructor.
MAY_NOT_CONTAIN - Enum constant in enum class edu.cmu.tetrad.calculator.parser.ExpressionParser.RestrictionType
The expression may not contain parameters in the given list.
MAY_ONLY_CONTAIN - Enum constant in enum class edu.cmu.tetrad.calculator.parser.ExpressionParser.RestrictionType
The expression may only contain parameters in the given list.
MB - Static variable in class edu.cmu.tetrad.util.Params
Constant MB="mb"
MbUtils - Class in edu.cmu.tetrad.search.utils
Provides some useful utilities for dealing with Markov blankets and Markov blanket DAGs.
mean(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
mean.
mean(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
mean.
mean(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
mean.
mean(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
mean.
mean(Matrix) - Static method in class edu.cmu.tetrad.data.DataUtils
mean.
mean(Vector, int) - Static method in class edu.cmu.tetrad.util.StatUtils
mean.
MEAN - Enum constant in enum class edu.cmu.tetrad.sem.ParamType
Variable Mean parameter type for SEM models.
MEAN - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Constant MEAN=2
MEAN - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.history.SimpleRandomizer
Indicates mean indegree.
MEAN_HIGH - Static variable in class edu.cmu.tetrad.util.Params
Constant MEAN_HIGH="meanHigh"
MEAN_LOW - Static variable in class edu.cmu.tetrad.util.Params
Constant MEAN_LOW="meanLow"
meanAbsolute(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
meanAbsolute.
MeanInterpolator - Class in edu.cmu.tetrad.data
Returns a data set in which missing values in each column are filled using the mean of that column.
MeanInterpolator() - Constructor for class edu.cmu.tetrad.data.MeanInterpolator
Constructor for MeanInterpolator.
means() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
means.
means(double[][]) - Static method in class edu.cmu.tetrad.data.DataUtils
Column major data.
means(Matrix) - Static method in class edu.cmu.tetrad.data.DataUtils
means.
MEASURED - Enum constant in enum class edu.cmu.tetrad.graph.NodeType
Constant MEASURED
MEASURED_MEASURED_IMPURE_ASSOCIATIONS - Static variable in class edu.cmu.tetrad.util.Params
Constant MEASURED_MEASURED_IMPURE_ASSOCIATIONS="measuredMeasuredImpureAssociations"
MEASURED_MEASURED_IMPURE_PARENTS - Static variable in class edu.cmu.tetrad.util.Params
Constant MEASURED_MEASURED_IMPURE_PARENTS="measuredMeasuredImpureParents"
MEASUREMENT_MODEL_DEGREE - Static variable in class edu.cmu.tetrad.util.Params
Constant MEASUREMENT_MODEL_DEGREE="measurementModelDegree"
MEASUREMENT_VARIANCE - Static variable in class edu.cmu.tetrad.util.Params
Constant MEASUREMENT_VARIANCE="measurementVariance"
MeasurementSimulator - Class in edu.cmu.tetrad.study.gene.tetrad.gene.simulation
Simulates measurement genetic data using an underlying GeneHistory object to generate individual cell data.
MeasurementSimulator(Parameters) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Constructs a measurement simulator using the given history.
MeasurementSimulatorParams - Class in edu.cmu.tetrad.study.gene.tetradapp.model
Wraps MeasurementSimulator so that it may be used as a parameter object.
MeasurementSimulatorParams(Parameters) - Constructor for class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
Constructs a measurement simulator using the given history.
median(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
median.
median(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
median.
median(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
median.
median(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
median.
MeekRules - Class in edu.cmu.tetrad.search.utils
Implements Meek's complete orientation rule set for PC (Chris Meek (1995), "Causal inference and causal explanation orienting.
MeekRules() - Constructor for class edu.cmu.tetrad.search.utils.MeekRules
Constructs the MeekRules with no logging.
Memorable - Interface in edu.cmu.tetrad.util
Tags a session node as "memorable", so that it won't be forgotten when a model is destroyed.
Mgm - Class in edu.cmu.tetrad.algcomparison.algorithm.mixed
MGM.
Mgm - Class in edu.pitt.csb.mgm
Implementation of Lee and Hastie's (2012) pseudolikelihood method for learning Mixed Gaussian-Categorical Graphical Models Created by ajsedgewick on 7/15/15.
Mgm() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.mixed.Mgm
Constructor for Mgm.
Mgm(DoubleMatrix2D, DoubleMatrix2D, List<Node>, int[], double[]) - Constructor for class edu.pitt.csb.mgm.Mgm
Constructor for Mgm.
Mgm(DataSet, double[]) - Constructor for class edu.pitt.csb.mgm.Mgm
Constructor for Mgm.
MGM_PARAM1 - Static variable in class edu.cmu.tetrad.util.Params
Constant MGM_PARAM1="mgmParam1"
MGM_PARAM2 - Static variable in class edu.cmu.tetrad.util.Params
Constant MGM_PARAM2="mgmParam2"
MGM_PARAM3 - Static variable in class edu.cmu.tetrad.util.Params
Constant MGM_PARAM3="mgmParam3"
Mgm.MGMParams - Class in edu.pitt.csb.mgm
The parameters of the MGM model.
MGMParams() - Constructor for class edu.pitt.csb.mgm.Mgm.MGMParams
Default constructor
MGMParams(DoubleMatrix1D, int, int) - Constructor for class edu.pitt.csb.mgm.Mgm.MGMParams
copy params from flattened vector
MGMParams(DoubleMatrix2D, DoubleMatrix1D, DoubleMatrix2D, DoubleMatrix2D, DoubleMatrix1D, DoubleMatrix1D) - Constructor for class edu.pitt.csb.mgm.Mgm.MGMParams
nothing is copied here, all pointers back to inputs...
MGMParams(Mgm.MGMParams) - Constructor for class edu.pitt.csb.mgm.Mgm.MGMParams
copy from another parameter set
MGMWrapper(double...) - Constructor for class edu.pitt.csb.stability.SearchWrappers.MGMWrapper
should be array three parameters for lambdas of each edge type
MillisecondTimes - Class in edu.cmu.tetrad.util
Reports elapsed time in wall time, user time, and CPU time in milliseconds.
MillisecondTimes.Type - Enum Class in edu.cmu.tetrad.util
An enum for the type of time.
Mimbuild - Class in edu.cmu.tetrad.search
Provides an implementation of Mimbuild, an algorithm that takes a clustering of variables, each of which is explained by a single latent, then forms the implied covariance matrix over the latent variables, then runs a CPDAG search to in the structure over the latent themselves.
Mimbuild() - Constructor for class edu.cmu.tetrad.search.Mimbuild
Constructs a new Mimbuild search.
MimbuildTrek - Class in edu.cmu.tetrad.search
Implements Mimbuild using the theory of treks and ranks.
MimbuildTrek() - Constructor for class edu.cmu.tetrad.search.MimbuildTrek
Empty constructor.
mimClusters(Graph) - Static method in class edu.cmu.tetrad.search.utils.ClusterUtils
Converts a list of indices into a list of Nodes representing a cluster.
MimUtils - Class in edu.cmu.tetrad.search.utils
Provides some utility methods for Purify, Build Clusters, and Mimbuild.
min(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
min.
min(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
min.
min(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
min.
min(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
min.
MIN_CATEGORIES - Static variable in class edu.cmu.tetrad.util.Params
Constant MIN_CATEGORIES="minCategories"
MIN_COUNT_PER_CELL - Static variable in class edu.cmu.tetrad.util.Params
Constant MIN_COUNT_PER_CELL="minCountPerCell"
MIN_FLOAT - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Minimum float value
MIN_INT - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Minimum int value
MIN_SAMPLE_SIZE_PER_CELL - Static variable in class edu.cmu.tetrad.util.Params
Constant COMPARE_GRAPH_ALGCOMP="compareGraphAlgcomp"
MIN_SHORT - Static variable in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Minimum short getValue
minCoveringSet(SortedSet[][]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch
minCoveringSet.
minus(Matrix) - Method in class edu.cmu.tetrad.util.Matrix
minus.
minus(Vector) - Method in class edu.cmu.tetrad.util.Vector
minus.
MisclassificationUtils - Class in edu.cmu.tetrad.graph
Some utilities for generating misclassification tables for graphs.
MISSING_VALUE - Static variable in class edu.cmu.tetrad.data.DiscreteVariable
This is the index in the data which represents missing data internally for this variable.
Mixed - Enum constant in enum class edu.cmu.tetrad.data.DataType
Mixed.
Mixed - Annotation Interface in edu.cmu.tetrad.annotation
Data with variables that have linear relationship.
MixedDataBox - Class in edu.cmu.tetrad.data
Stores a 2D array of double continuousData.
MixedDataBox(List<Node>, int) - Constructor for class edu.cmu.tetrad.data.MixedDataBox
The variables here are used only to determine which columns are discrete and which are continuous; bounds checking is not done.
MixedDataBox(List<Node>, int, double[][], int[][]) - Constructor for class edu.cmu.tetrad.data.MixedDataBox
This constructor allows other data readers to populate the fields directly.
MixedUtils - Class in edu.pitt.csb.mgm
Created by ajsedgewick on 7/29/15.
MixtureModel - Class in edu.cmu.tetrad.search.work_in_progress
Represents a Gaussian mixture model -- a dataset with data sampled from two or more multivariate Gaussian distributions.
MixtureModel(DataSet, double[][], double[][], double[], Matrix[], double[][]) - Constructor for class edu.cmu.tetrad.search.work_in_progress.MixtureModel
Constructs a mixture model from a mixed data set, a means matrix, a weights array, a variance matrix, and a gamma matrix.
MixtureOfGaussians - Class in edu.cmu.tetrad.util.dist
Wraps a chi square distribution for purposes of drawing random samples.
MixtureOfGaussians(double, double, double, double, double) - Constructor for class edu.cmu.tetrad.util.dist.MixtureOfGaussians
Constructor for MixtureOfGaussians.
mkRandSEMDAG(int, int) - Static method in class edu.cmu.tetrad.simulation.HsimUtils
mkRandSEMDAG.
MlBayesEstimator - Class in edu.cmu.tetrad.bayes
Estimates parameters of the given Bayes net from the given data using maximum likelihood method.
MlBayesEstimator(double) - Constructor for class edu.cmu.tetrad.bayes.MlBayesEstimator
Create an instance of MlBayesEstimator with the given prior.
MlBayesEstimatorOld - Class in edu.cmu.tetrad.bayes
Estimates parameters of the given Bayes net from the given data using maximum likelihood method.
MlBayesEstimatorOld() - Constructor for class edu.cmu.tetrad.bayes.MlBayesEstimatorOld
Constructor for MlBayesEstimator.
MlBayesIm - Class in edu.cmu.tetrad.bayes
Stores a table of probabilities for a Bayes net and, together with BayesPm and Dag, provides methods to manipulate this table.
MlBayesIm(BayesIm) - Constructor for class edu.cmu.tetrad.bayes.MlBayesIm
Copy constructor.
MlBayesIm(BayesPm) - Constructor for class edu.cmu.tetrad.bayes.MlBayesIm
Constructs a new BayesIm from the given BayesPm, initializing all values as Double.NaN ("?").
MlBayesIm(BayesPm, boolean) - Constructor for class edu.cmu.tetrad.bayes.MlBayesIm
Constructs an instance of MlBayesIm.
MlBayesIm(BayesPm, BayesIm, MlBayesIm.InitializationMethod) - Constructor for class edu.cmu.tetrad.bayes.MlBayesIm
Constructs a new BayesIm from the given BayesPm, initializing values either as MANUAL or RANDOM, but using values from the old BayesIm provided where posssible.
MlBayesIm(BayesPm, MlBayesIm.InitializationMethod) - Constructor for class edu.cmu.tetrad.bayes.MlBayesIm
Constructs a new BayesIm from the given BayesPm, initializing values either as MANUAL or RANDOM.
MlBayesIm.CptMapType - Enum Class in edu.cmu.tetrad.bayes
An enumeration representing the different types of CptMap.
MlBayesIm.InitializationMethod - Enum Class in edu.cmu.tetrad.bayes
The InitializationMethod enum represents different methods of initializing a class object.
MlBayesImObs - Class in edu.cmu.tetrad.bayes
Stores a table of probabilities for a Bayes net and, together with BayesPm and Dag, provides methods to manipulate this table.
MlBayesImObs(BayesIm) - Constructor for class edu.cmu.tetrad.bayes.MlBayesImObs
Constructor for MlBayesImObs.
MlBayesImObs(BayesPm) - Constructor for class edu.cmu.tetrad.bayes.MlBayesImObs
Constructs a new BayesIm from the given BayesPm, initializing all values as Double.NaN ("?").
MlBayesImObs(BayesPm, int) - Constructor for class edu.cmu.tetrad.bayes.MlBayesImObs
Constructs a new BayesIm from the given BayesPm, initializing values either as MANUAL or RANDOM.
MlBayesImObs(BayesPm, BayesIm, int) - Constructor for class edu.cmu.tetrad.bayes.MlBayesImObs
Constructs a new BayesIm from the given BayesPm, initializing values either as MANUAL or RANDOM, but using values from the old BayesIm provided where posssible.
Mmhc - Class in edu.cmu.tetrad.search.work_in_progress
Implements the MMHC algorithm.
Mmhc(IndependenceTest, DataSet) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Mmhc
Constructor for Mmhc.
Mmmb - Class in edu.cmu.tetrad.search.work_in_progress
Implements the Min-Max Markov Blanks (MMMB) algorithm as defined in Tsamardinos, Aliferis, and Statnikov, Time and Sample Efficient Discovery of Markov Blankets and Direct Causal Relations (KDD 2003).
Mmmb(IndependenceTest, int, boolean) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Mmmb
Constructs.
MnlrLikelihood - Class in edu.cmu.tetrad.search.work_in_progress
Calculates Mixed Variables Polynomial likelihood.
MnlrLikelihood(DataSet, double, int) - Constructor for class edu.cmu.tetrad.search.work_in_progress.MnlrLikelihood
Constructor.
Mnlrlrt - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Fisher Z test.
Mnlrlrt() - Constructor for class edu.cmu.tetrad.algcomparison.independence.Mnlrlrt
Constructs a new instance of the test.
MnlrScore - Class in edu.cmu.tetrad.search.work_in_progress
Implements a mixed variable polynomial BIC score for fGES.
MnlrScore(DataSet, double, int) - Constructor for class edu.cmu.tetrad.search.work_in_progress.MnlrScore
Constructor.
ModeInterpolator - Class in edu.cmu.tetrad.bayes
Creates a data set in which missing values in each column are filled using the mode of that column.
ModeInterpolator() - Constructor for class edu.cmu.tetrad.bayes.ModeInterpolator
Constructor for ModeInterpolator.
ModelGenerator - Class in edu.cmu.tetrad.bayes
Provides static methods for generating variants of an input graph.
ModelObserver - Interface in edu.cmu.tetrad.search
The ModelObserver interface is implemented by classes that want to observe changes in a model.
modifiedR0(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Modifies the given FGES graph based on the FCI algorithm rules, reorienting edges and potentially identifying and orienting definite colliders.
moralize(Graph) - Static method in class edu.cmu.tetrad.bayes.GraphTools
Create a moral graph.
Move(Edge, Edge, HbsmsBeam.Move.Type) - Constructor for class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move
Constructor for Move.
Move(Edge, HbsmsBeam.Move.Type) - Constructor for class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move
Constructor for Move.
moveTo(Node, int) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Moves v to a new index.
moveToEnd() - Method in interface edu.cmu.tetrad.util.TetradLogger.LogDisplayOutputStream
Should move the log to the end of the stream.
MSeparationScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for Fisher Z test.
MSeparationScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.MSeparationScore
Use this empty constructor to satisfy the java reflection
MSeparationScore(Graph) - Constructor for class edu.cmu.tetrad.algcomparison.score.MSeparationScore
Constructor for MSeparationScore.
MSeparationTest - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for M-separation test.
MSeparationTest() - Constructor for class edu.cmu.tetrad.algcomparison.independence.MSeparationTest
Use this empty constructor to satisfy the java reflection
MSeparationTest(Graph) - Constructor for class edu.cmu.tetrad.algcomparison.independence.MSeparationTest
Constructor for MSeparationTest.
MsepTest - Class in edu.cmu.tetrad.search.test
Checks independence facts for variables associated with the nodes in a given graph by checking m-separation facts on the underlying nodes.
MsepTest(IndependenceFacts) - Constructor for class edu.cmu.tetrad.search.test.MsepTest
Constructor.
MsepTest(IndependenceFacts, boolean) - Constructor for class edu.cmu.tetrad.search.test.MsepTest
Constructor.
MsepTest(IndependenceFacts, List<Node>) - Constructor for class edu.cmu.tetrad.search.test.MsepTest
Constructor.
MsepTest(Graph) - Constructor for class edu.cmu.tetrad.search.test.MsepTest
Constructor.
MsepTest(Graph, boolean) - Constructor for class edu.cmu.tetrad.search.test.MsepTest
Constructor.
mu(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
mu.
mu(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
mu.
mu(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
mu.
mu(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
mu.
mudholkergeorge - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Mudholker and George's method
mudholkergeorge - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
The mudholkergeorge method.
mudholkergeorge2 - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Mudholker and George's method
mudholkergeorge2 - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
The mudholkergeorge2 method.
muHat(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
muHat.
muHat(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
muHat.
muHat(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
muHat.
muHat(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
muHat.
MultiDataSetAlgorithm - Interface in edu.cmu.tetrad.algcomparison.algorithm
Implements an algorithm that takes multiple data sets as input.
MultidataUtils - Class in edu.cmu.tetrad.util
Aug 7, 2018 10:21:59 AM
MultiDimIntTable - Class in edu.cmu.tetrad.util
Stores a table of cells with int values of arbitrary dimension.
MultiDimIntTable(int[]) - Constructor for class edu.cmu.tetrad.util.MultiDimIntTable
Constructs a new multidimensional table of integer cells, with the given (fixed) dimensions.
MultiGeneralAndersonDarlingTest - Class in edu.cmu.tetrad.data
Implements the Anderson-Darling test against the given CDF, with P values calculated as in R's ad.test method (in package nortest).
MultiGeneralAndersonDarlingTest(List<List<Double>>, List<RealDistribution>) - Constructor for class edu.cmu.tetrad.data.MultiGeneralAndersonDarlingTest
Constructs an Anderson-Darling test for the given column of data.
MultinomialLogisticRegressionWald - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Fisher Z test.
MultinomialLogisticRegressionWald() - Constructor for class edu.cmu.tetrad.algcomparison.independence.MultinomialLogisticRegressionWald
Constructs a new instance of the test.
multinormalProb(double[], double[], double[][]) - Static method in class edu.cmu.tetrad.util.ProbUtils
Compute the probability over a rectangular region with correlation matrix c.
multOuter(Vector, Vector) - Static method in class edu.cmu.tetrad.util.TetradAlgebra
multOuter.
mutualInformation(int, int[], int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealEvaluator
This method computes the mutual information between a gene and a set of presumptive causes (other genes).
mutualInformation(int, int[], int) - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.LTestReveal
mutualInformation.
mutualInformation(int, int[], int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealEvaluator
This method computes the mutual information between a gene and a set of presumptive causes (other genes).
mutualInformation(int, int[], int[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealEvaluator
This method computes the mutual information between a gene and a set of presumptive causes (other genes).
MVPBicScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for MVP BIC Score.
MVPBicScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.MVPBicScore
Constructs a new instance of the score.
MVPCompareFromFiles - Class in edu.cmu.tetrad.algcomparison.examples
An example script to load in data sets and graphs from files and analyze them.
MVPCompareFromFiles() - Constructor for class edu.cmu.tetrad.algcomparison.examples.MVPCompareFromFiles
Constructor for MVPCompareFromFiles.
MvpLikelihood - Class in edu.cmu.tetrad.search.score
Calculates Mixed Variables Polynomial likelihood.
MvpLikelihood(DataSet, double, int, boolean) - Constructor for class edu.cmu.tetrad.search.score.MvpLikelihood
Constructs the score using a data set.
Mvplrt - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Fisher Z test.
Mvplrt() - Constructor for class edu.cmu.tetrad.algcomparison.independence.Mvplrt
Constructs a new instance of the test.
MvpScore - Class in edu.cmu.tetrad.search.score
Implements a mixed variable polynomial BIC score.
MvpScore(DataSet, double, int, boolean) - Constructor for class edu.cmu.tetrad.search.score.MvpScore
Constructor.
MyContext() - Constructor for class edu.cmu.tetrad.sem.GeneralizedSemEstimator.MyContext
Constructs a new MyContext.

N

N(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
N.
N(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
N.
name() - Element in annotation interface edu.cmu.tetrad.annotation.Algorithm
Name of the algorithm.
name() - Element in annotation interface edu.cmu.tetrad.annotation.Score
The name of the score.
name() - Element in annotation interface edu.cmu.tetrad.annotation.TestOfIndependence
Name of the test.
NamingProtocol - Class in edu.cmu.tetrad.util
Specifies the protocol used in Tetrad for variable names.
NANDY - Enum constant in enum class edu.cmu.tetrad.search.score.GicScores.RuleType
BIC using Nandy et al.'s formulation.
NANDY - Enum constant in enum class edu.cmu.tetrad.search.score.SemBicScore.RuleType
The formulation of the standard BIC score given in Nandy et al.
nandyBic(int, int, int[]) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Calculates the BIC score of a partial correlation based on the specified variables.
NbComponent - Interface in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
NbComponent interface.
NbFunction - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
NbFunction class.
NbFunction(double, double, NbComponent[], int[], String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbFunction
Constructor for NbFunction.
NbFunctionAnd - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
NbFunctionAnd class.
NbFunctionAnd(double, double, NbComponent[], int[], String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbFunctionAnd
Constructor for NbFunctionAnd.
NbFunctionOr - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
NbFunctionOr class.
NbFunctionOr(double, double, NbComponent[], int[], String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbFunctionOr
Constructor for NbFunctionOr.
NbFunctionSum - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
NbFunctionSum class.
NbFunctionSum(double, double, NbComponent[], int[], String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbFunctionSum
Constructor for NbFunctionSum.
NbFunctionSV - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
NbFunctionSV class.
NbFunctionSV(double, double, NbComponent[], int[], String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbFunctionSV
Constructor for NbFunctionSV.
NbGene - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
NbGene class.
NbGene(double, double, NbComponent[], int[], String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbGene
Constructor for NbGene.
NbGeneAnd - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
NbGeneAnd class.
NbGeneAnd(double, double, NbComponent[], int[], String, double) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbGeneAnd
Constructor for NbGeneAnd.
NbGeneOr - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
NbGeneOr class.
NbGeneOr(double, double, NbComponent[], int[], String, double) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbGeneOr
Constructor for NbGeneOr.
NC - Enum constant in enum class edu.cmu.tetrad.sem.ParamComparison
Represents the "Non-comparable" comparison type for a parameter in SEM estimation.
negativeInfinity() - Static method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Score
negativeInfinity.
NEITHER - Enum constant in enum class edu.cmu.tetrad.calculator.expression.ExpressionDescriptor.Position
The expression can occur in neither the prefix nor infix position.
NetBuilderModel - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
NetBuilderModel class.
NetBuilderModel(double[], int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NetBuilderModel
Constructor for NetBuilderModel.
NEWLINE - Static variable in class edu.pitt.isp.sverchkov.data.DataTools
Constant NEWLINE="System.getProperty(line.separator)"
next() - Method in class edu.cmu.tetrad.search.utils.DagInCpcagIterator
Successive calls to this method return successive DAGs in the CPDAG, in a more or less natural enumeration of them in which an arbitrary undirected edge is picked, oriented one way, Meek rules applied, then a remaining unoriented edge is picked, oriented one way, and so on, until a DAG is obtained, and then by backtracking the other orientation of each chosen edge is tried.
next() - Method in class edu.cmu.tetrad.search.utils.DagIterator
Successive calls to this method return successive DAGs in the CPDAG, in a more or less natural enumeration of them in which an arbitrary undirected edge is picked, oriented one way, Meek rules applied, then a remaining unoriented edge is picked, oriented one way, and so on, until a DAG is obtained, and then by backtracking the other orientation of each chosen edge is tried.
next() - Method in class edu.cmu.tetrad.util.ChoiceGenerator
next.
next() - Method in class edu.cmu.tetrad.util.CombinationGenerator
next.
next() - Method in class edu.cmu.tetrad.util.CombinationIterator
next.
next() - Method in class edu.cmu.tetrad.util.PermutationGenerator
next.
next() - Method in class edu.cmu.tetrad.util.SelectionGenerator
next.
next() - Method in class edu.cmu.tetrad.util.SublistGenerator
next.
nextBeta(double, double) - Method in class edu.cmu.tetrad.util.RandomUtil
nextBeta.
nextChiSquare(double) - Method in class edu.cmu.tetrad.util.RandomUtil
nextChiSquare.
nextDouble() - Method in class edu.cmu.tetrad.util.RandomUtil
nextDouble.
nextExponential(double) - Method in class edu.cmu.tetrad.util.RandomUtil
nextExponential.
nextGamma(double, double) - Method in class edu.cmu.tetrad.util.RandomUtil
nextGamma.
nextGumbel(double, double) - Method in class edu.cmu.tetrad.util.RandomUtil
nextGumbel.
nextIncrementalRelease() - Method in class edu.cmu.tetrad.util.Version
nextIncrementalRelease.
nextInt(int) - Method in class edu.cmu.tetrad.util.RandomUtil
nextInt.
nextLong() - Method in class edu.cmu.tetrad.util.RandomUtil
nextLong.
nextMajorVersion() - Method in class edu.cmu.tetrad.util.Version
nextMajorVersion.
nextMinorSubversion() - Method in class edu.cmu.tetrad.util.Version
nextMinorSubversion.
nextMinorVersion() - Method in class edu.cmu.tetrad.util.Version
nextMinorVersion.
nextNormal(double, double) - Method in class edu.cmu.tetrad.util.RandomUtil
nextNormal.
nextParameterName(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Given base b (a String), returns the first name in the sequence "b1", "b2", "b3", etc., which is not already the name of a node in the workbench.
nextPoisson(double) - Method in class edu.cmu.tetrad.util.RandomUtil
nextPoisson.
nextRandom() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.RandomDistribution
Draws a new noise value from the underlying distribution.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.Beta
Returns the next random.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.ChiSquare
nextRandom.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.Discrete
nextRandom.
nextRandom() - Method in interface edu.cmu.tetrad.util.dist.Distribution
Returns the next random number from the distribution.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.Exponential
nextRandom.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.Gamma
nextRandom.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.GaussianPower
nextRandom.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.Indicator
nextRandom.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.LogNormal
nextRandom.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.MixtureOfGaussians
nextRandom.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.Normal
nextRandom.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.Poisson
nextRandom.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.SingleValue
Returns the next random number from the distribution.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.Split
nextRandom.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.TruncatedNormal
nextRandom.
nextRandom() - Method in class edu.cmu.tetrad.util.dist.Uniform
nextRandom.
nextT(double) - Method in class edu.cmu.tetrad.util.RandomUtil
nextT.
nextToken() - Method in class edu.cmu.tetrad.calculator.parser.ExpressionLexer
nextToken.
nextToken() - Method in class edu.cmu.tetrad.data.RegexTokenizer
nextToken.
nextTokenIncludingWhitespace() - Method in class edu.cmu.tetrad.calculator.parser.ExpressionLexer
nextTokenIncludingWhitespace.
nextTruncatedNormal(double, double, double, double) - Method in class edu.cmu.tetrad.util.RandomUtil
nextTruncatedNormal.
nextUniform(double, double) - Method in class edu.cmu.tetrad.util.RandomUtil
nextUniform.
nil - Enum constant in enum class edu.cmu.tetrad.graph.EdgeTypeProbability.EdgeType
No edge
nl - Enum constant in enum class edu.cmu.tetrad.graph.Edge.Property
No latent confounder.
NLSemSimulation - Class in edu.cmu.tetrad.algcomparison.simulation
NL SEM simulation.
NLSemSimulation(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.NLSemSimulation
Constructor for NLSemSimulation.
NO_RANDOMLY_DETERMINED_INDEPENDENCE - Static variable in class edu.cmu.tetrad.util.Params
Constant NO_RANDOMLY_DETERMINED_INDEPENDENCE="noRandomlyDeterminedIndependence"
NO_TYPE - Enum constant in enum class edu.cmu.tetrad.graph.NodeType
Constant NO_TYPE
NoAlmostCyclicPathsCondition - Class in edu.cmu.tetrad.algcomparison.statistic
No almost cyclic paths condition.
NoAlmostCyclicPathsCondition() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NoAlmostCyclicPathsCondition
Constructs a new instance of the statistic.
NoCyclicPathsCondition - Class in edu.cmu.tetrad.algcomparison.statistic
No cyclic paths condition.
NoCyclicPathsCondition() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NoCyclicPathsCondition
Constructs a new instance of the statistic.
Node - Interface in edu.cmu.tetrad.graph
Represents an object with a name, node type, and position that can serve as a node in a graph.
NodeId(String, int) - Constructor for class edu.cmu.tetrad.graph.TimeLagGraph.NodeId
Constructor for NodeId.
NodePair - Class in edu.cmu.tetrad.graph
An unordered pair of nodes.
NodePair(Node, Node) - Constructor for class edu.cmu.tetrad.graph.NodePair
Constructor for NodePair.
NodesInCyclesPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
NodesInCyclesPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesPrecision
Constructs a new instance of the statistic.
NodesInCyclesRecall - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
NodesInCyclesRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesRecall
Constructs a new instance of the statistic.
NodeType - Enum Class in edu.cmu.tetrad.graph
An enum of the node types in a graph (MEASURED, LATENT, ERROR).
NodeVariableType - Enum Class in edu.cmu.tetrad.graph
Node variable type.
noEdgeRequired(String, String) - Method in class edu.cmu.tetrad.data.Knowledge
noEdgeRequired.
NOMINAL - Static variable in class edu.cmu.tetrad.data.DiscreteVariableType
Constant NOMINAL
NON_LINEAR_STRUCTURAL_EQUATION_MODEL - Static variable in class edu.cmu.tetrad.algcomparison.simulation.SimulationTypes
Constant NON_LINEAR_STRUCTURAL_EQUATION_MODEL="Non-Linear Structural Equation Model"
NonancestorPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
Number of NOT X~~>Y in true graph for which also NOT X~~>Y in estimated graph.
NonancestorPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NonancestorPrecision
Constructs a new instance of the statistic.
NonancestorRecall - Class in edu.cmu.tetrad.algcomparison.statistic
Number of NOT X~~>Y in true graph for which also NOT X~~>Y in estimated graph.
NonancestorRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NonancestorRecall
Constructs a new instance of the statistic.
NONCOLLIDER - Enum constant in enum class edu.cmu.tetrad.search.utils.GraphSearchUtils.CpcTripleType
A noncollider triple.
NONCOLLIDER - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.VcPc.CpcTripleType
The triple is a noncollider.
NONCOLLIDER - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.VcPcFast.CpcTripleType
Constant NONCOLLIDER
NONCOLLIDERS_ONLY - Enum constant in enum class edu.cmu.tetrad.search.ConditioningSetType
Conditioning on noncolliders only.
nondirectedEdge(Node, Node) - Static method in class edu.cmu.tetrad.graph.Edges
Constructs a new nondirected edge from nodeA to nodeB (o-o).
nondirectedGraph(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
undirectedGraph.
None - Enum constant in enum class edu.cmu.tetrad.search.utils.ClusterSignificance.CheckType
Do not do the check.
NONE - Enum constant in enum class edu.cmu.tetrad.calculator.parser.ExpressionParser.RestrictionType
The expression may contain any parameters.
NONE - Enum constant in enum class edu.cmu.tetrad.search.FaskOrig.AdjacencyMethod
No initial adjacencies.
NONE - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
This option doesn't do any purify.
NONE - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.PcHeuristicType
No heuristic.
NONE - Enum constant in enum class edu.cmu.tetrad.sem.ParamConstraintType
Represents a parameter constraint type NONE.
NONE - Static variable in class edu.cmu.tetrad.data.ContinuousDiscretizationSpec
Constant NONE=3
Nonexecutable - Annotation Interface in edu.cmu.tetrad.annotation
Indicates an algorithm is nonexecutable.
nonSmooth(double, DoubleMatrix1D, DoubleMatrix1D) - Method in class edu.pitt.csb.mgm.ConvexProximal
Calculate value of h(X) and proxOperator of h(X) at the same time for efficiency reasons.
nonSmooth(double, DoubleMatrix1D, DoubleMatrix1D) - Method in class edu.pitt.csb.mgm.Mgm
Calculates the non-smooth value for a given parameter and input vectors.
nonSmoothValue(DoubleMatrix1D) - Method in class edu.pitt.csb.mgm.Mgm
Calculates the non-smooth value for the given input vector.
norm1() - Method in class edu.cmu.tetrad.util.Matrix
norm1.
norm2(DoubleMatrix1D) - Static method in class edu.pitt.csb.mgm.ProximalGradient
norm2.
Normal - Class in edu.cmu.tetrad.util.dist
A normal distribution that allows its parameters to be set and allows random sampling.
Normal(double, double) - Constructor for class edu.cmu.tetrad.util.dist.Normal
Constructor for Normal.
normalCdf(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
Normal cumulative distribution function (the value which results by integrating the normal distribution function from negative infinity up to y).
normalCdf(double, double, double) - Method in class edu.cmu.tetrad.util.RandomUtil
normalCdf.
normalizeAll() - Method in interface edu.cmu.tetrad.bayes.BayesIm
Normalizes all rows in the tables associated with each of node in turn.
normalizeAll() - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Normalizes all rows in the tables associated with each of node in turn.
normalizeAll() - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Normalizes all rows in the tables associated with each of node in turn.
normalizeAll() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Normalizes all rows in the tables associated with each of node in turn.
normalizeAll() - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
normalizeAll.
normalizeNode(int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Normalizes all rows in the table associated with a given node.
normalizeNode(int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Normalizes all rows in the table associated with a given node.
normalizeNode(int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Normalizes the specified node by invoking the MlBayesIm.normalizeRow(int, int) method on each row of the node.
normalizeNode(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Normalizes all rows in the table associated with a given node.
normalizeNode(int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Normalizes all rows in the table associated with a given node.
normalizeRow(int, int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Normalizes the given row.
normalizeRow(int, int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Normalizes the given row.
normalizeRow(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Normalizes the probabilities of a given row in a node.
normalizeRow(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Normalizes the given row.
normalizeRow(int, int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Normalizes the given row.
normalPdf(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
normalPdf.
normalPdf(double, double, double) - Method in class edu.cmu.tetrad.util.RandomUtil
normalPdf.
normalQuantile(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
normalQuantile.
normalRand() - Static method in class edu.cmu.tetrad.util.ProbUtils
Normal random generator
NoSemidirectedF1 - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the F1 statistic for adjacencies.
NoSemidirectedF1() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedF1
Constructs a new instance of the statistic.
NoSemidirectedPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NoSemidirectedPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedPrecision
Constructs a new instance of the statistic.
NoSemidirectedRecall - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NoSemidirectedRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedRecall
Constructs a new instance of the statistic.
notifyObservers() - Method in class edu.cmu.tetrad.search.MarkovCheck
Notifies all registered ModelObservers by invoking their update() method.
nRooks(boolean[][]) - Static method in class edu.cmu.tetrad.search.utils.NRooks
Solves the N-Rooks problem for the given board or allowable positions.
NRooks - Class in edu.cmu.tetrad.search.utils
Returns row positions for placing rooks for an n x n matrix so the rooks cannot attach each other, with a given boolean[][] specification of where rooks are allowed to be placed.
NULL - Enum constant in enum class edu.cmu.tetrad.graph.Endpoint
No endpoint.
NUM_BASIS_FUNCTIONS - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_BASIS_FUNCTIONS="numBasisFunctions"
NUM_BSC_BOOTSTRAP_SAMPLES - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_BSC_BOOTSTRAP_SAMPLES="numBscBootstrapSamples"
NUM_CATEGORIES - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_CATEGORIES="numCategories"
NUM_CATEGORIES_TO_DISCRETIZE - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_CATEGORIES_TO_DISCRETIZE="numCategoriesToDiscretize"
NUM_LAGS - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_LAGS="numLags"
NUM_LATENTS - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_LATENTS="numLatents"
NUM_MEASURES - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_MEASURES="numMeasures"
NUM_RANDOMIZED_SEARCH_MODELS - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_RANDOMIZED_SEARCH_MODELS="numRandomizedSearchModels"
NUM_ROUNDS - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_ROUNDS="numRounds"
NUM_RUNS - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_RUNS="numRuns"
NUM_STARTS - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_STARTS="numStarts"
NUM_STRUCTURAL_EDGES - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_STRUCTURAL_EDGES="numStructuralEdges"
NUM_STRUCTURAL_NODES - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_STRUCTURAL_NODES="numStructuralNodes"
NUM_SUBSAMPLES - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_SUBSAMPLES="numSubsamples"
NUM_THREADS - Static variable in class edu.cmu.tetrad.util.Params
Constant NUM_THREADS="numThreads"
NumAmbiguousTriples - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
NumAmbiguousTriples() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumAmbiguousTriples
Constructs a new instance of the statistic.
NUMBER - Enum constant in enum class edu.cmu.tetrad.calculator.parser.Token
Number.
NUMBER_OF_EXPANSIONS - Static variable in class edu.cmu.tetrad.util.Params
Constant NUMBER_OF_EXPANSIONS="numberOfExpansions"
NUMBER_RESAMPLING - Static variable in class edu.cmu.tetrad.util.Params
Constant NUMBER_RESAMPLING="numberResampling"
NumberArrowsEst - Class in edu.cmu.tetrad.algcomparison.statistic
Represents the NumberEdgesEst statistic, which calculates the number of arrows in the estimated graph.
NumberArrowsEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsEst
Constructs the statistic.
NumberArrowsNotInUnshieldedCollidersEst - Class in edu.cmu.tetrad.algcomparison.statistic
Represents the NumberEdgesEst statistic, which calculates the number of arrows not in unshielded colliders in the estimated graph.
NumberArrowsNotInUnshieldedCollidersEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsNotInUnshieldedCollidersEst
Constructs the statistic.
NumberCollidersEst - Class in edu.cmu.tetrad.algcomparison.statistic
Represents the NumberEdgesEst statistic, which calculates the number of unshielded colliders in the estimated graph.
NumberCollidersEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumberCollidersEst
Constructs the statistic.
NumberEdgesEst - Class in edu.cmu.tetrad.algcomparison.statistic
Represents the NumberEdgesEst statistic, which calculates the number of edges in the estimated graph.
NumberEdgesEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesEst
Constructs the statistic.
NumberEdgesInCollidersEst - Class in edu.cmu.tetrad.algcomparison.statistic
Represents the NumberEdgesEst statistic, which calculates the number of edges in colliders in the estimated graph.
NumberEdgesInCollidersEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInCollidersEst
Constructs the statistic.
NumberEdgesInUnshieldedCollidersEst - Class in edu.cmu.tetrad.algcomparison.statistic
Represents the NumberEdgesEst statistic, which calculates the number of edges in unshielded colliders in the estimated graph.
NumberEdgesInUnshieldedCollidersEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInUnshieldedCollidersEst
Constructs the statistic.
NumberEdgesTrue - Class in edu.cmu.tetrad.algcomparison.statistic
The NumberEdgesTrue class is an implementation of the Statistic interface.
NumberEdgesTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesTrue
Constructs the statistic.
NumberFormatUtil - Class in edu.cmu.tetrad.util
Provides an application-wide "memory" of the number format to be used.
NumberObjectDataSet - Class in edu.cmu.tetrad.data
Wraps a 2D array of Number objects in such a way that mixed data sets can be stored.
NumberObjectDataSet(Number[][], List<Node>) - Constructor for class edu.cmu.tetrad.data.NumberObjectDataSet
Constructor for NumberObjectDataSet.
NumberOfEdgesEst - Class in edu.cmu.tetrad.algcomparison.statistic
Prints the number of edges in the estimated graph.
NumberOfEdgesEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesEst
Constructs a new instance of the statistic.
NumberOfEdgesTrue - Class in edu.cmu.tetrad.algcomparison.statistic
Prints the number of edges in the true graph.
NumberOfEdgesTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesTrue
Constructs a new instance of the statistic.
NumberTailsEst - Class in edu.cmu.tetrad.algcomparison.statistic
Represents the NumberEdgesEst statistic, which calculates the number of tails in the estimated graph.
NumberTailsEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumberTailsEst
Constructs the statistic.
NumberUnshieldedCollidersEst - Class in edu.cmu.tetrad.algcomparison.statistic
Represents the NumberEdgesEst statistic, which calculates the number of unshielded colliders in the estimated graph.
NumberUnshieldedCollidersEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumberUnshieldedCollidersEst
Constructs the statistic.
NumBidirectedBothNonancestorAncestor - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected edge precision.
NumBidirectedBothNonancestorAncestor() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedBothNonancestorAncestor
Constructs a new instance of the statistic.
NumBidirectedEdgesEst - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
NumBidirectedEdgesEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesEst
Constructs a new instance of the statistic.
NumBidirectedEdgesTrue - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
NumBidirectedEdgesTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesTrue
Constructs a new instance of the statistic.
NumColoredDD - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumColoredDD() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumColoredDD
Constructs a new instance of the statistic.
NumColoredNL - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumColoredNL() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumColoredNL
Constructs a new instance of the statistic.
NumColoredPD - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumColoredPD() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumColoredPD
Constructs a new instance of the statistic.
NumColoredPL - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumColoredPL() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumColoredPL
Constructs a new instance of the statistic.
numCols() - Method in class edu.cmu.tetrad.data.ByteDataBox
numCols.
numCols() - Method in interface edu.cmu.tetrad.data.DataBox
numCols.
numCols() - Method in class edu.cmu.tetrad.data.DoubleDataBox
numCols.
numCols() - Method in class edu.cmu.tetrad.data.FloatDataBox
numCols.
numCols() - Method in class edu.cmu.tetrad.data.IntDataBox
numCols.
numCols() - Method in class edu.cmu.tetrad.data.LongDataBox
numCols.
numCols() - Method in class edu.cmu.tetrad.data.MixedDataBox
numCols.
numCols() - Method in class edu.cmu.tetrad.data.ShortDataBox
numCols.
numCols() - Method in class edu.cmu.tetrad.data.VerticalDoubleDataBox
numCols.
numCols() - Method in class edu.cmu.tetrad.data.VerticalIntDataBox
numCols.
NumCommonMeasuredAncestorBidirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumCommonMeasuredAncestorBidirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCommonMeasuredAncestorBidirected
Constructs a new instance of the statistic.
NumCompatibleDefiniteDirectedEdgeAncestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumCompatibleDefiniteDirectedEdgeAncestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDefiniteDirectedEdgeAncestors
Constructs a new instance of the statistic.
NumCompatibleDirectedEdgeConfounded - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumCompatibleDirectedEdgeConfounded() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeConfounded
Constructs a new instance of the statistic.
NumCompatibleDirectedEdgeNonAncestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumCompatibleDirectedEdgeNonAncestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeNonAncestors
Constructs a new instance of the statistic.
NumCompatibleEdges - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumCompatibleEdges() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleEdges
Constructs a new instance of the statistic.
NumCompatiblePossiblyDirectedEdgeAncestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumCompatiblePossiblyDirectedEdgeAncestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeAncestors
Constructs a new instance of the statistic.
NumCompatiblePossiblyDirectedEdgeNonAncestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumCompatiblePossiblyDirectedEdgeNonAncestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeNonAncestors
Constructs a new instance of the statistic.
NumCompatibleVisibleNonancestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumCompatibleVisibleNonancestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleVisibleNonancestors
Constructs a new instance of the statistic.
NumCorrectBidirected - Class in edu.cmu.tetrad.algcomparison.statistic
Counts the number of X<->Y edges for which a latent confounder of X and Y exists.
NumCorrectBidirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCorrectBidirected
Counts the number of bidirectional edges for which a latent confounder of X and Y exists.
NumCorrectDDAncestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumCorrectDDAncestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCorrectDDAncestors
Constructs a new instance of the statistic.
NumCorrectPDAncestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumCorrectPDAncestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCorrectPDAncestors
Constructs a new instance of the statistic.
NumCorrectVisibleEdges - Class in edu.cmu.tetrad.algcomparison.statistic
Represents a statistic that calculates the number of correct visible ancestors in the true graph that are also visible ancestors in the estimated graph.
NumCorrectVisibleEdges() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCorrectVisibleEdges
Constructs a new instance of the statistic.
NumCoveringAdjacenciesInPag - Class in edu.cmu.tetrad.algcomparison.statistic
The number of covering adjacencies in an estimated PAG compared to the true PAG.
NumCoveringAdjacenciesInPag() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumCoveringAdjacenciesInPag
Constructs the statistic.
NumDefinitelyDirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumDefinitelyDirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyDirected
Constructs a new instance of the statistic.
NumDefinitelyNotDirectedPaths - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumDefinitelyNotDirectedPaths() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyNotDirectedPaths
Constructs a new instance of the statistic.
NumDirectedEdgeAncestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumDirectedEdgeAncestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeAncestors
Constructs a new instance of the statistic.
NumDirectedEdgeBnaMeasuredCounfounded - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumDirectedEdgeBnaMeasuredCounfounded() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeBnaMeasuredCounfounded
Constructs a new instance of the statistic.
NumDirectedEdgeNoMeasureAncestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumDirectedEdgeNoMeasureAncestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNoMeasureAncestors
Constructs a new instance of the statistic.
NumDirectedEdgeNotAncNotRev - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumDirectedEdgeNotAncNotRev() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNotAncNotRev
Constructs a new instance of the statistic.
NumDirectedEdgeReversed - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumDirectedEdgeReversed() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeReversed
Constructs a new instance of the statistic.
NumDirectedEdges - Class in edu.cmu.tetrad.algcomparison.statistic
Number of X-->Y in est.
NumDirectedEdges() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdges
Constructs a new instance of the statistic.
NumDirectedPathsEst - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumDirectedPathsEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsEst
Constructs a new instance of the statistic.
NumDirectedPathsTrue - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumDirectedPathsTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsTrue
Constructs a new instance of the statistic.
NumDirectedShouldBePartiallyDirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumDirectedShouldBePartiallyDirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumDirectedShouldBePartiallyDirected
Constructs a new instance of the statistic.
NumEdgeInEstInTrue - Class in edu.cmu.tetrad.algcomparison.statistic
The number of adjacencies in the estimated graph but not in the true graph.
NumEdgeInEstInTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumEdgeInEstInTrue
Constructs the statistic.
NumGenuineAdjacenciesInPag - Class in edu.cmu.tetrad.algcomparison.statistic
The number of genuine adjacencies in an estimated PAG compared to the true PAG.
NumGenuineAdjacenciesInPag() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumGenuineAdjacenciesInPag
Constructs the statistic.
NumIncorrectDDAncestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumIncorrectDDAncestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectDDAncestors
Constructs a new instance of the statistic.
NumIncorrectPDAncestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumIncorrectPDAncestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectPDAncestors
Constructs a new instance of the statistic.
NumIncorrectVisibleAncestors - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumIncorrectVisibleAncestors() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectVisibleAncestors
Constructs a new instance of the statistic.
NumLatentCommonAncestorBidirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumLatentCommonAncestorBidirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumLatentCommonAncestorBidirected
Constructs a new instance of the statistic.
NumNondirectedEdges - Class in edu.cmu.tetrad.algcomparison.statistic
Number of X---Y in est.
NumNondirectedEdges() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumNondirectedEdges
Constructs a new instance of the statistic.
numParameters(int, int[]) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
Returns the number of parameters for a node given its parents.
NumParametersEst - Class in edu.cmu.tetrad.algcomparison.statistic
Number of parameters for a discrete Bayes model of the data.
NumParametersEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumParametersEst
Constructor for NumParametersEst.
NumPartiallyOrientedEdges - Class in edu.cmu.tetrad.algcomparison.statistic
Number of Xo->Y in est.
NumPartiallyOrientedEdges() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumPartiallyOrientedEdges
Constructs a new instance of the statistic.
NumPossiblyDirected - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
NumPossiblyDirected() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumPossiblyDirected
Constructs a new instance of the statistic.
numRows() - Method in class edu.cmu.tetrad.data.ByteDataBox
numRows.
numRows() - Method in interface edu.cmu.tetrad.data.DataBox
numRows.
numRows() - Method in class edu.cmu.tetrad.data.DoubleDataBox
numRows.
numRows() - Method in class edu.cmu.tetrad.data.FloatDataBox
numRows.
numRows() - Method in class edu.cmu.tetrad.data.IntDataBox
numRows.
numRows() - Method in class edu.cmu.tetrad.data.LongDataBox
numRows.
numRows() - Method in class edu.cmu.tetrad.data.MixedDataBox
numRows.
numRows() - Method in class edu.cmu.tetrad.data.ShortDataBox
numRows.
numRows() - Method in class edu.cmu.tetrad.data.VerticalDoubleDataBox
numRows.
numRows() - Method in class edu.cmu.tetrad.data.VerticalIntDataBox
numRows.
numTestsDep() - Method in record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Returns the value of the numTestsDep record component.
numTestsInd() - Method in record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Returns the value of the numTestsInd record component.
NumUndirectedEdges - Class in edu.cmu.tetrad.algcomparison.statistic
Number of X---Y in est.
NumUndirectedEdges() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumUndirectedEdges
Constructs a new instance of the statistic.
numVals(DoubleMatrix1D) - Static method in class edu.pitt.csb.mgm.MixedUtils
numVals.
NumVisibleEdgeEst - Class in edu.cmu.tetrad.algcomparison.statistic
NumVisibleEdgeEst is a class that implements the Statistic interface.
NumVisibleEdgeEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdgeEst
Constructs a new instance of the statistic.
NumVisibleEdges - Class in edu.cmu.tetrad.algcomparison.statistic
Represents a statistic that calculates the number of correct visible ancestors in the true graph that are also visible ancestors in the estimated graph.
NumVisibleEdges() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdges
Constructs a new instance of the statistic.
NumVisibleEdgeTrue - Class in edu.cmu.tetrad.algcomparison.statistic
A class that implements the Statistic interface to calculate the number of visible edges in the true PAG.
NumVisibleEdgeTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdgeTrue
A class that calculates the number of visible edges in the true PAG.

O

oneFactorTest(int, int, int, int) - Method in interface edu.cmu.tetrad.search.utils.TetradTest
oneFactorTest.
oneFactorTest(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
oneFactorTest.
oneFactorTest(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
oneFactorTest.
oneFactorTest(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
oneFactorTest.
oneFactorTest(int, int, int, int, int) - Method in interface edu.cmu.tetrad.search.utils.TetradTest
oneFactorTest.
oneFactorTest(int, int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
oneFactorTest.
oneFactorTest(int, int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
oneFactorTest.
oneFactorTest(int, int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
oneFactorTest.
OPERATOR - Enum constant in enum class edu.cmu.tetrad.calculator.parser.Token
Operator.
optimize(SemIm) - Method in interface edu.cmu.tetrad.sem.SemOptimizer
Optimizes the fitting function of a Sem by adjusting its parameter values.
optimize(SemIm) - Method in class edu.cmu.tetrad.sem.SemOptimizerEm
Optimizes an unoptimized Sem object by minimizing the chi-square statistic.
optimize(SemIm) - Method in class edu.cmu.tetrad.sem.SemOptimizerPowell
Optimizes the fitting function of a Sem by adjusting its parameter values.
optimize(SemIm) - Method in class edu.cmu.tetrad.sem.SemOptimizerRegression
Optimizes the fitting function of a Sem by adjusting its parameter values.
optimize(SemIm) - Method in class edu.cmu.tetrad.sem.SemOptimizerRicf
Optimizes the fitting function of a Sem by adjusting its parameter values.
optimize(SemIm) - Method in class edu.cmu.tetrad.sem.SemOptimizerScattershot
Optimizes the fitting function of a Sem by adjusting its parameter values.
ORDERED_LOCAL_MARKOV - Enum constant in enum class edu.cmu.tetrad.search.ConditioningSetType
Testing independence facts implied by the graph, conditioning on the parents of each variable in the graph, in a causal order of the graph.
OrderedPair<E> - Class in edu.cmu.tetrad.graph
An ordered pair of objects.
OrderedPair(E, E) - Constructor for class edu.cmu.tetrad.graph.OrderedPair
Constructor for OrderedPair.
orient() - Method in class edu.cmu.tetrad.search.Lofs
Orients the graph and returns the oriented graph.
orient(Graph) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
orient.
orient(Graph) - Method in class edu.cmu.tetrad.search.utils.MaxP
Adds colliders to the given graph using the max P rule.
orient(Graph, Set<Triple>) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Performs FCI orientation on the given graph, including R0 and either the Spirtes or Zhang final orientation rules.
ORIENT_BIDIRECTED - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.ConflictRule
When there is a conflict, orient a bidirected edge.
orient_pairwise - Enum constant in enum class edu.cmu.tetrad.annotation.AlgType
If algorithm orients edges pairwise.
ORIENT_TOWARD_DCONNECTIONS - Static variable in class edu.cmu.tetrad.util.Params
Constant ORIENT_TOWARD_DCONNECTIONS="orientTowardDConnections"
ORIENT_VISIBLE_FEEDBACK_LOOPS - Static variable in class edu.cmu.tetrad.util.Params
Constant ORIENT_VISIBLE_FEEDBACK_LOOPS="orientVisibleFeedbackLoops"
ORIENTATION_ALPHA - Static variable in class edu.cmu.tetrad.util.Params
Constant ORIENTATION_ALPHA="orientationAlpha"
OrientationConfusion - Class in edu.cmu.tetrad.algcomparison.statistic.utils
A confusion matrix for orientations:
OrientationConfusion(Graph, Graph) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.utils.OrientationConfusion
Constructor for OrientationConfusion.
OrientationPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The orientation precision.
OrientationPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.OrientationPrecision
Constructs a new instance of the statistic.
OrientationRecall - Class in edu.cmu.tetrad.algcomparison.statistic
Represents an implementation of the Statistic interface that calculates the Orientation Recall.
OrientationRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.OrientationRecall
Constructs a new instance of the statistic.
orientCollider(Node, Node, Node, PcCommon.ConflictRule, Graph, boolean) - Static method in class edu.cmu.tetrad.search.utils.PcCommon
Orient a single unshielded triple, x*-*y*-*z, in a graph.
orientCollidersUsingSepsets(SepsetMap, Knowledge, Graph, boolean, boolean) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Step C of PC; orients colliders using specified sepset.
orientImplied(Graph) - Method in class edu.cmu.tetrad.search.utils.MeekRules
Uses the Meek rules to do as many orientations in the given graph as possible.
other - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Score
Other score.
outerProduct(double[], double[]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
outerProduct.
OUTPUT_CPDAG - Static variable in class edu.cmu.tetrad.util.Params
Constant OUTPUT_CPDAG="outputCpdag"
OUTPUT_RBD - Static variable in class edu.cmu.tetrad.util.Params
Constant OUTPUT_RBD="outputRBD"
OutputGraph - Interface in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util
Represents a graph that's output by a genetic search algorithm.
OVERWRITE_EXISTING - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.ConflictRule
When there is a conflict, use the new orientation.

P

p - Variable in class edu.cmu.tetrad.bayes.BayesProperties.LikelihoodRet
The p-value.
PAG - Enum constant in enum class edu.cmu.tetrad.graph.GraphUtils.GraphType
The PAG graph type.
PAG - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.ResultType
Constant for PAG result type.
PAG_of_the_true_DAG - Enum constant in enum class edu.cmu.tetrad.algcomparison.Comparison.ComparisonGraph
Constant for the PAG of the true DAG.
PAG_of_the_true_DAG - Enum constant in enum class edu.cmu.tetrad.algcomparison.TimeoutComparison.ComparisonGraph
The pag of the true dag.
PAG_SAMPLING_RFCI_PARAMETERS - Static variable in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci
Constant PAG_SAMPLING_RFCI_PARAMETERS
PagAdjacencyPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The PagAdjacencyPrecision class implements the Statistic interface and represents the adjacency precision compared to the true PAG (Partially Ancestral Graph).
PagAdjacencyPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyPrecision
Constructs a new instance of the statistic.
PagAdjacencyRecall - Class in edu.cmu.tetrad.algcomparison.statistic
A class that implements the PagAdjacencyRecall statistic.
PagAdjacencyRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyRecall
Constructs a new instance of the statistic.
PagCache - Class in edu.cmu.tetrad.util
A cache for storing PAGs so that the only need to be calculated once per DAG.
PagSampleRfci - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
Jan 29, 2023 3:45:09 PM
PagSampleRfci() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci
Constructs a new instance of the PagSampleRfci algorithm.
PagSamplingRfci - Class in edu.pitt.dbmi.algo.bayesian.constraint.search
Jan 29, 2023 4:10:52 PM
PagSamplingRfci(DataSet) - Constructor for class edu.pitt.dbmi.algo.bayesian.constraint.search.PagSamplingRfci
Constructor.
PARALLEL - Enum constant in enum class edu.cmu.tetrad.search.LvLite.ExtraEdgeRemovalStyle
Remove extra edges in parallel.
PARALLEL - Static variable in class edu.cmu.tetrad.search.FastIca
The algorithm type where all components are extracted simultaneously.
PARALLELIZED - Static variable in class edu.cmu.tetrad.util.Params
Constant PARALLELIZED="parallelized"
ParamComparison - Enum Class in edu.cmu.tetrad.sem
An enum of the types of the various comparisons a parameter may have with respect to one another for SEM estimation.
ParamConstraint - Class in edu.cmu.tetrad.sem
A class for implementing constraints on the values of the freeParameters of of instances of the SemIm class.
ParamConstraint(SemIm, Parameter, ParamConstraintType, double) - Constructor for class edu.cmu.tetrad.sem.ParamConstraint
The first constructor specifies the parameter and a number and the type of relation imposed by the constraint.
ParamConstraintType - Enum Class in edu.cmu.tetrad.sem
Enum for representing different types of parameter constraints.
ParamDescription - Class in edu.cmu.tetrad.util
Describes a parameter.
ParamDescription(String, String, String, Serializable) - Constructor for class edu.cmu.tetrad.util.ParamDescription
Constructor for ParamDescription.
ParamDescription(String, String, String, Serializable, double, double) - Constructor for class edu.cmu.tetrad.util.ParamDescription
Constructor for ParamDescription.
ParamDescription(String, String, String, Serializable, int, int) - Constructor for class edu.cmu.tetrad.util.ParamDescription
Constructor for ParamDescription.
ParamDescriptions - Class in edu.cmu.tetrad.util
Stores descriptions of the parameters for the simulation box.
Parameter - Class in edu.cmu.tetrad.sem
Stores information about the identity of a SEM parameter--its name, its type (COEF, COVAR), and the node(s) it is associated with.
Parameter(String, ParamType, Node, Node) - Constructor for class edu.cmu.tetrad.sem.Parameter
Constructor for Parameter.
PARAMETER - Enum constant in enum class edu.cmu.tetrad.calculator.parser.Token
Parameter.
ParameterColumn - Class in edu.cmu.tetrad.algcomparison.statistic
Adds a column to the output table in which values for the given parameter are listed.
ParameterColumn(String) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ParameterColumn
Constructor for ParameterColumn.
ParameterPair - Class in edu.cmu.tetrad.sem
Implements an ordered pair of objects (a, b) suitable for storing in HashSets.
ParameterPair(Parameter, Parameter) - Constructor for class edu.cmu.tetrad.sem.ParameterPair
Constructs a new ordered pair (a, b).
ParameterRange(Edge, double, double, double) - Constructor for class edu.cmu.tetrad.sem.StandardizedSemIm.ParameterRange
Constructs a new parameter range.
Parameters - Class in edu.cmu.tetrad.util
Stores a list of named parameters with their values.
Parameters() - Constructor for class edu.cmu.tetrad.util.Parameters
Constructor for Parameters.
Parameters(Parameters) - Constructor for class edu.cmu.tetrad.util.Parameters
Constructor for Parameters.
ParameterUtils - Class in edu.cmu.tetrad.util
A utility to create/modify parameters.
parameterValues() - Method in interface edu.cmu.tetrad.algcomparison.utils.ParameterValues
parameterValues.
parameterValues() - Method in class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph
parameterValues.
ParameterValues - Interface in edu.cmu.tetrad.algcomparison.utils
Tags a class that can return values for parameters.
Params - Class in edu.cmu.tetrad.util
May 7, 2019 2:53:27 PM
ParamType - Enum Class in edu.cmu.tetrad.sem
An enum of the free parameter types for SEM models (COEF, MEAN, VAR, COVAR).
parent(Node, Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
parent.
PARENTS_AND_NEIGHBORS - Enum constant in enum class edu.cmu.tetrad.search.ConditioningSetType
Conditioning on the parents and neighbors of each variable in the graph.
parseEquation(String) - Method in class edu.cmu.tetrad.calculator.parser.ExpressionParser
Parses an equation of the form Variable = Expression.
parseExpression(String) - Method in class edu.cmu.tetrad.calculator.parser.ExpressionParser
Parses the given expression, or throws an exception if its not possible.
parseGraphXml(Element, Map<String, Node>) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
parseGraphXml.
parseJSONArrayToTetradEdges(Graph, JSONArray) - Static method in class edu.cmu.tetrad.util.JsonUtils
parseJSONArrayToTetradEdges.
parseJSONArrayToTetradNodes(JSONArray) - Static method in class edu.cmu.tetrad.util.JsonUtils
parseJSONArrayToTetradNodes.
parseJSONArrayToTetradTriple(JSONObject) - Static method in class edu.cmu.tetrad.util.JsonUtils
parseJSONArrayToTetradTriple.
parseJSONArrayToTetradTriples(JSONArray) - Static method in class edu.cmu.tetrad.util.JsonUtils
parseJSONArrayToTetradTriples.
parseJSONObjectToEdgeProperty(String) - Static method in class edu.cmu.tetrad.util.JsonUtils
parseJSONObjectToEdgeProperty.
parseJSONObjectToEdgeTypeProperty(JSONObject) - Static method in class edu.cmu.tetrad.util.JsonUtils
parseJSONObjectToEdgeTypeProperty.
parseJSONObjectToTetradEdge(Graph, JSONObject) - Static method in class edu.cmu.tetrad.util.JsonUtils
parseJSONObjectToTetradEdge.
parseJSONObjectToTetradGraph(String) - Static method in class edu.cmu.tetrad.util.JsonUtils
parseJSONObjectToTetradGraph.
parseJSONObjectToTetradGraph(JSONObject) - Static method in class edu.cmu.tetrad.util.JsonUtils
parseJSONObjectToTetradGraph.
parseJSONObjectToTetradNode(JSONObject) - Static method in class edu.cmu.tetrad.util.JsonUtils
parseJSONObjectToTetradNode.
partialCorrelation(Matrix) - Static method in class edu.cmu.tetrad.util.StatUtils
Assumes that the given covariance matrix was extracted in such a way that the order of the variables (in either direction) is X, Y, Z1, ..., Zn, where the partial correlation one wants is correlation(X, Y | Z1,...,Zn).
partialCorrelation(Matrix, int, int, int...) - Static method in class edu.cmu.tetrad.util.StatUtils
partialCorrelation.
PartialCorrelation - Class in edu.cmu.tetrad.search.utils
Calculates partial correlation using the recursive method.
PartialCorrelation(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.search.utils.PartialCorrelation
Constructor
PartialCorrelation(List<Node>, Matrix, int) - Constructor for class edu.cmu.tetrad.search.utils.PartialCorrelation
Constructor.
PartialCorrelationPdf - Class in edu.cmu.tetrad.util
Frequency function of partial correlation r(12|34...k), assuming that the true partial correlation is equal to zero.
PartialCorrelationPdf(int, int) - Constructor for class edu.cmu.tetrad.util.PartialCorrelationPdf
Constructs a new zero partial correlation distribution function with the given values for n and k.
partialCorrelationPrecisionMatrix(Matrix) - Static method in class edu.cmu.tetrad.util.StatUtils
partialCorrelationPrecisionMatrix.
partialCovarianceWhittaker(Matrix) - Static method in class edu.cmu.tetrad.util.StatUtils
Assumes that the given covariance matrix was extracted in such a way that the order of the variables (in either direction) is X, Y, Z1, ..., Zn, where the partial covariance one wants is covariance(X, Y | Z1,...,Zn).
partialCovarianceWhittaker(Matrix, int, int, int...) - Static method in class edu.cmu.tetrad.util.StatUtils
partialCovarianceWhittaker.
partiallyOrientedEdge(Node, Node) - Static method in class edu.cmu.tetrad.graph.Edges
Constructs a new partially oriented edge from nodeA to nodeB (o->).
partialStandardDeviation(Matrix, int, int...) - Static method in class edu.cmu.tetrad.util.StatUtils
partialStandardDeviation.
partialVariance(Matrix, int, int...) - Static method in class edu.cmu.tetrad.util.StatUtils
partialVariance.
partitionToClusters(List<List<Node>>) - Static method in class edu.cmu.tetrad.search.utils.ClusterUtils
Converts a list of indices into a list of Nodes representing a cluster.
Patel - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The Patel rule.
Patel25 - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The Patel25 rule.
Patel50 - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The Patel50 rule.
Patel75 - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The Patel75 rule.
Patel90 - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The Patel90 rule.
paths() - Method in class edu.cmu.tetrad.graph.Dag
paths.
paths() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
paths.
paths() - Method in interface edu.cmu.tetrad.graph.Graph
paths.
paths() - Method in class edu.cmu.tetrad.graph.LagGraph
paths.
paths() - Method in class edu.cmu.tetrad.graph.SemGraph
paths.
paths() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns the instance of Paths.
Paths - Class in edu.cmu.tetrad.graph
Paths class.
Paths(Graph) - Constructor for class edu.cmu.tetrad.graph.Paths
Constructor for Paths.
Paths.AllCliquesAlgorithm - Class in edu.cmu.tetrad.graph
An algorithm to find all cliques in a graph.
pathString(Graph, Node...) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Generates a string representation of a path in a given graph, starting from the specified nodes.
pathString(Graph, Node, Node, Node) - Static method in class edu.cmu.tetrad.graph.Triple
pathString.
pathString(Graph, List<Node>, boolean) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Constructs a string representation of a path in a graph.
pathString(Graph, List<Node>, Set<Node>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns a string representation of the given path in the graph, considering the conditioning variables.
pathString(Graph, List<Node>, Set<Node>, boolean, boolean) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Returns a string representation of the given path in the graph, with additional information about conditioning variables.
Pc - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
Peter/Clark algorithm (PC).
Pc - Class in edu.cmu.tetrad.search
Implements the Peter/Clark (PC) algorithm, which uses conditional independence testing as an oracle to first of all remove extraneous edges from a complete graph, then to orient the unshielded colliders in the graph, and finally to make any additional orientations that are capable of avoiding additional unshielded colliders in the graph.
Pc() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pc
Constructor for Pc.
Pc(IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pc
Constructor for Pc.
Pc(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.Pc
Constructs a new PC search using the given independence test as oracle.
PC - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.Algorithm
Constant for the PC algorithm.
PC_HEURISTIC - Static variable in class edu.cmu.tetrad.util.Params
Constant PC_HEURISTIC="pcHeuristic"
PC_STABLE - Enum constant in enum class edu.cmu.tetrad.search.Cstar.CpdagAlgorithm
The PC_STABLE algorithm.
PcCommon - Class in edu.cmu.tetrad.search.utils
Provides some common implementation pieces of various PC-like algorithms, with options for collider discovery type, FAS type, and conflict rule.
PcCommon(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.utils.PcCommon
Constructs a CPC algorithm that uses the given independence test as oracle.
PcCommon.ColliderDiscovery - Enum Class in edu.cmu.tetrad.search.utils
Gives the options for the collider discovery algorithm to use--FAS with sepsets reasoning, FAS with conservative reasoning, or FAS with Max P reasoning.
PcCommon.ConflictRule - Enum Class in edu.cmu.tetrad.search.utils
Gives the type of conflict to be used, priority (when there is a conflict, keep the orientation that has already been made), bidirected (when there is a conflict, orient a bidirected edge), or overwrite (when there is a conflict, use the new orientation).
PcCommon.FasType - Enum Class in edu.cmu.tetrad.search.utils
Gives the type of FAS used, regular or stable.
PcCommon.PcHeuristicType - Enum Class in edu.cmu.tetrad.search.utils
The PC heuristic type, where this is taken from Causation, Prediction, and Search.
Pcd - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
PC.
Pcd - Class in edu.cmu.tetrad.search
Modifies the PC algorithm to handle the deterministic case.
Pcd() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pcd
Constructor for Pcd.
Pcd(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.Pcd
Constructs a new PC search using the given independence test as oracle.
pcdOrientC(IndependenceTest, Knowledge, Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Performs step C of the algorithm, as indicated on page xxx of CPS, with the modification that X--W--Y is oriented as X-->W<--Y if W is *determined by* the sepset of (X, Y), rather than W just being *in* the sepset of (X, Y).
PcMb - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
PC.
PcMb - Class in edu.cmu.tetrad.search
Searches for a CPDAG representing all the Markov blankets for a given target T consistent with the given independence information.
PcMb() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMb
Constructor for PcMb.
PcMb(IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMb
Constructor for PcMb.
PcMb(IndependenceTest, int) - Constructor for class edu.cmu.tetrad.search.PcMb
Constructs a new search.
pcOrientbk(Knowledge, Graph, List<Node>, boolean) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Orients according to background knowledge.
PcStableWrapper(double...) - Constructor for class edu.pitt.csb.stability.SearchWrappers.PcStableWrapper
Constructor.
pd - Enum constant in enum class edu.cmu.tetrad.graph.Edge.Property
Possibly direct.
PENALTY_DISCOUNT - Static variable in class edu.cmu.tetrad.util.Params
Constant PENALTY_DISCOUNT="penaltyDiscount"
PENALTY_DISCOUNT_ZS - Static variable in class edu.cmu.tetrad.util.Params
Constant PENALTY_DISCOUNT_ZS="penaltyDiscountZs"
PERCENT_DISCRETE - Static variable in class edu.cmu.tetrad.util.Params
Constant PERCENT_DISCRETE="percentDiscrete"
PERCENT_RESAMPLE_SIZE - Static variable in class edu.cmu.tetrad.util.Params
Constant PERCENT_RESAMPLE_SIZE="percentResampleSize"
PercentAmbiguous - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
PercentAmbiguous() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.PercentAmbiguous
Constructs a new instance of the statistic.
PercentBidirectedEdges - Class in edu.cmu.tetrad.algcomparison.statistic
The adjacency precision.
PercentBidirectedEdges() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.PercentBidirectedEdges
Constructs a new instance of the statistic.
PerformanceTests - Class in edu.cmu.tetrad.study.performance
Runs some basic performance tests of various algorithm.
PerformanceTests() - Constructor for class edu.cmu.tetrad.study.performance.PerformanceTests
This class represents a set of performance tests for a certain application.
PerformanceTestsDan - Class in edu.cmu.tetrad.study.performance
Contains some tests for Dan Malinsky, that might be of interest to others.
PerformanceTestsDan() - Constructor for class edu.cmu.tetrad.study.performance.PerformanceTestsDan
Constructor for PerformanceTestsDan.
PermutationGenerator - Class in edu.cmu.tetrad.util
Generates all of the permutations of [0,..., numObjects - 1], where numObjects is numObjects nonnegative integer.
PermutationGenerator(int) - Constructor for class edu.cmu.tetrad.util.PermutationGenerator
Constructs numObjects new choice generator for numObjects choose b.
PermutationMatrixPair - Class in edu.cmu.tetrad.search.utils
Stores a matrix together with a row and column permutation.
PermutationMatrixPair(Matrix, int[], int[]) - Constructor for class edu.cmu.tetrad.search.utils.PermutationMatrixPair
Constructs with a given matrix M and a row and column permutation (which may be null).
PermutationSearch - Class in edu.cmu.tetrad.search
Implements common elements of a permutation search.
PermutationSearch(SuborderSearch) - Constructor for class edu.cmu.tetrad.search.PermutationSearch
Constructs a new PermutationSearch using the given SuborderSearch.
permutationTest(Node, Node, Set<Node>, int) - Method in class edu.cmu.tetrad.search.test.ConditionalCorrelationIndependence
Performs a permutation test to empirically determine the distribution of p-values under the null hypothesis.
permuteRows() - Method in class edu.cmu.tetrad.data.BoxDataSet
Randomly permutes the rows of the dataset.
permuteRows() - Method in interface edu.cmu.tetrad.data.DataSet
Randomizes the rows of the data set.
permuteRows() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Randomly permutes the rows of the dataset.
PI - Static variable in class edu.cmu.tetrad.calculator.expression.ConstantExpression
Constant expression for PI.
pl - Enum constant in enum class edu.cmu.tetrad.graph.Edge.Property
Possible latent confounder.
plus(Matrix) - Method in class edu.cmu.tetrad.util.Matrix
plus.
plus(Vector) - Method in class edu.cmu.tetrad.util.Vector
plus.
Pm - Interface in edu.cmu.tetrad.util
Tagging interface for parametric models.
Point - Class in edu.cmu.tetrad.util
Implements an n-dimensional point.
Point(Vector) - Constructor for class edu.cmu.tetrad.util.Point
Constructs a point with coordinates as in the given vector.
pointsTowards(Node) - Method in class edu.cmu.tetrad.graph.Edge
pointsTowards.
PointXy - Class in edu.cmu.tetrad.util
Stores a (x, y) point without having to use awt classes.
PointXy(int, int) - Constructor for class edu.cmu.tetrad.util.PointXy
Constructs a new point with the given coordinates.
PointXy(PointXy) - Constructor for class edu.cmu.tetrad.util.PointXy
Copy constructor.
poisson(double, double, boolean) - Static method in class edu.cmu.tetrad.util.StatUtils
Calculates the Poisson Distribution for mean x and k events for doubles.
Poisson - Class in edu.cmu.tetrad.util.dist
Wraps a chi square distribution for purposes of drawing random samples.
POISSON_LAMBDA - Static variable in class edu.cmu.tetrad.util.Params
Constant POISSON_LAMBDA="poissonLambda"
poissonCdf(int, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
poissonCdf.
poissonPmf(int, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
poissonPmf.
PoissonPriorScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for the Poisson prior score (Bryan)
PoissonPriorScore - Class in edu.cmu.tetrad.search.score
Implements Poisson prior score, a novel (unpubished) score that replaces the penalty term in BIC by the log of the Poisson distribution.
PoissonPriorScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.PoissonPriorScore
Constructs a new instance of the PoissonPriorScore.
PoissonPriorScore(DataSet, boolean) - Constructor for class edu.cmu.tetrad.search.score.PoissonPriorScore
Constructs the score using a covariance matrix.
PoissonPriorScore(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.search.score.PoissonPriorScore
Constructs the score using a covariance matrix.
PoissonPriorTest - Class in edu.cmu.tetrad.algcomparison.independence
 
PoissonPriorTest() - Constructor for class edu.cmu.tetrad.algcomparison.independence.PoissonPriorTest
Constructs a new instance of the Poisson Prior test.
poissonQuantile(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
poissonQuantile.
poissonRand(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
Poisson random generator from Numerical Recipes
Polynomial - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Implements a polynomial as a sum of a list of terms whose variables are identified as integers in the set {0, 1, 2, ...}.
Polynomial(List<PolynomialTerm>) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.Polynomial
Constructs a polynomial from a list of terms.
POLYNOMIAL - Enum constant in enum class edu.cmu.tetrad.search.test.Kci.KernelType
 
POLYNOMIAL_CONSTANT - Static variable in class edu.cmu.tetrad.util.Params
Constant POLYNOMIAL_CONSTANT="polynomialConstant"
POLYNOMIAL_DEGREE - Static variable in class edu.cmu.tetrad.util.Params
Constant POLYNOMIAL_DEGREE="polynomialDegree"
PolynomialFunction - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Implements a polynomial update function, Gi.0 = P(Parents(G0.0)) + ei, where P is a polynomial function and ei is a random noise term.
PolynomialFunction(LagGraph) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialFunction
Constructs a polyomial function where each factor is given a zero polynomial.
PolynomialTerm - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Implements a term in a polymonial whose variables are mapped to indices in in the set {0, 1, 2, ...}.
PolynomialTerm(double, int[]) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialTerm
Constructs a term.
POPULATION - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
Population test.
PositiveCorr - Class in edu.cmu.tetrad.algcomparison.independence
Wrapper for Fisher Z test.
PositiveCorr() - Constructor for class edu.cmu.tetrad.algcomparison.independence.PositiveCorr
Constructs a new instance of the FisherZTest.
PositiveCorrScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for Fisher Z test.
PositiveCorrScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.PositiveCorrScore
Constructs a new instance of the FisherZScore.
POSSIBLE_MSEP_DONE - Static variable in class edu.cmu.tetrad.util.Params
Constant POSSIBLE_MSEP_DONE="possibleMsepDone"
possibleAncestor(Node, Node) - Method in class edu.cmu.tetrad.graph.Paths
possibleAncestor.
possibleDsep(Node, Node, int) - Method in class edu.cmu.tetrad.graph.Paths
Calculates the possible d-separation nodes between two given Nodes within a graph, using a maximum path length constraint.
PossibleMConnectingPath - Class in edu.cmu.tetrad.search.utils
Finds possible d-connecting undirectedPaths for the IonSearch.
PossibleMsepFci - Class in edu.cmu.tetrad.search.utils
Implements the Possible-M-Sep search step of Spirtes, et al's (1993) FCI algorithm (pp 144-145).
PossibleMsepFci(Graph, IndependenceTest) - Constructor for class edu.cmu.tetrad.search.utils.PossibleMsepFci
Creates a new SepSet and assumes that none of the variables have yet been checked.
pow() - Static method in class edu.cmu.tetrad.util.StatUtils
pow.
powerSet(List<Node>) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
powerSet.
PRAOerrors - Class in edu.cmu.tetrad.simulation
Created by Erich on 8/21/2016.
PRAOerrors(double[], String) - Constructor for class edu.cmu.tetrad.simulation.PRAOerrors
Constructor for PRAOerrors.
PRAOerrors(List<PRAOerrors>, String) - Constructor for class edu.cmu.tetrad.simulation.PRAOerrors
Constructor for PRAOerrors.
PRECOMPUTE_COVARIANCES - Static variable in class edu.cmu.tetrad.util.Params
Constant PRECOMPUTE_COVARIANCES="precomputeCovariances"
predictor(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ItkPredictorSearch
predictor.
PREFIX - Enum constant in enum class edu.cmu.tetrad.calculator.expression.ExpressionDescriptor.Position
The expression can occur in the prefix position.
Preserved - Enum constant in enum class edu.pitt.dbmi.algo.resampling.ResamplingEdgeEnsemble
Choose an edge iff there is an edge that its prob.
PreviousStepOnly - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Initializes a graph by adding the previous time step only of each variable.
PreviousStepOnly() - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.PreviousStepOnly
Constructor for PreviousStepOnly.
printClusterPValues(Set<List<Integer>>) - Method in class edu.cmu.tetrad.search.utils.ClusterSignificance
Prints the p-values for the given clusters.
printEdges() - Method in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Prints the parent matrix for the graph.
printGraphDegrees() - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
printGraphDegrees.
printStuffForKlea() - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
printStuffForKlea.
PRIOR_EQUIVALENT_SAMPLE_SIZE - Static variable in class edu.cmu.tetrad.util.Params
Constant PRIOR_EQUIVALENT_SAMPLE_SIZE="priorEquivalentSampleSize"
PRIORITIZE_EXISTING - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.ConflictRule
When there is a conflict, keep the orientation that has already been made.
PROB_CYCLE - Static variable in class edu.cmu.tetrad.util.Params
Constant PROB_CYCLE="probCycle"
PROB_MAP - Enum constant in enum class edu.cmu.tetrad.bayes.MlBayesIm.CptMapType
Represents a probabilistic CptMap type.
PROB_REMOVE_COLUMN - Static variable in class edu.cmu.tetrad.util.Params
Constant PROB_REMOVE_COLUMN="probRemoveColumn"
PROB_TWO_CYCLE - Static variable in class edu.cmu.tetrad.util.Params
Constant PROB_TWO_CYCLE="probTwoCycle"
PROBABILISTIC_TEST_PARAMETERS - Static variable in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci
Constant PROBABILISTIC_TEST_PARAMETERS
ProbabilisticMapIndependence - Class in edu.cmu.tetrad.search.work_in_progress
Uses BCInference by Cooper and Bui to calculate probabilistic conditional independence judgments.
ProbabilisticMapIndependence(DataSet) - Constructor for class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
Initializes the test using a discrete data sets.
ProbabilisticTest - Class in edu.cmu.tetrad.algcomparison.independence
Dec 17, 2018 3:44:46 PM
ProbabilisticTest() - Constructor for class edu.cmu.tetrad.algcomparison.independence.ProbabilisticTest
Constructs a new instance of the ProbabilisticTest class.
probability(double) - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Calculates the probability mass function (PMF) of a given point.
PROBABILITY_OF_EDGE - Static variable in class edu.cmu.tetrad.util.Params
Constant PROBABILITY_OF_EDGE="probabilityOfEdge"
probConstraint(BCCausalInference.OP, int, int, int[]) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCCausalInference
This function takes a constraint, which has a value of either OP.dependent or OP.independent, of the form "X independent Y given Z" or "X dependent Y given Z" and returns a probability for that constraint given the data in cases and assumed prior probability for that constraint given the data in cases and assumed prior probabilities.
probConstraint(BCInference.OP, int, int, int[]) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCInference
This function takes a constraint, which has a value of either OP.dependent or OP.independent, of the form "X independent Y given Z" or "X dependent Y given Z" and returns a probability for that constraint given the data in cases and assumed prior probability for that constraint given the data in cases and assumed prior probabilities.
probConstraint(BCInference.OP, Node, Node, Node[]) - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
probConstraint.
probConstraint(BCInference, BCInference.OP, Node, Node, Node[], Map<Node, Integer>) - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Returns the probability of the constraint x op y | z.
ProbUtils - Class in edu.cmu.tetrad.util
Implements a number of important functions from probability and statistics.> 0
produce_undirected_graphs - Enum constant in enum class edu.cmu.tetrad.annotation.AlgType
If an algorithm produces undirected graphs.
product(double[][], double[]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
product.
product(double[][], double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
product.
product(double[], double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
product.
product(Vector, Matrix) - Static method in class edu.cmu.tetrad.util.MatrixUtils
product.
ProportionSemidirectedPathsNotReversedEst - Class in edu.cmu.tetrad.algcomparison.statistic
Proportion of semi(X, Y) in estimated graph for which there is no semi(Y, X) in true graph.
ProportionSemidirectedPathsNotReversedEst() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedEst
Constructs a new instance of the statistic.
ProportionSemidirectedPathsNotReversedTrue - Class in edu.cmu.tetrad.algcomparison.statistic
Proportion of semi(X, Y) in true graph for which there is no semi(Y, Z) in estimated graph.
ProportionSemidirectedPathsNotReversedTrue() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedTrue
Constructs a new instance of the statistic.
Proposition - Class in edu.cmu.tetrad.bayes
Represents propositions over the variables of a particular BayesIm describing an event of a fairly general sort--namely, conjunctions of propositions that particular variables take on values from a particular disjunctive list of categories.
Proposition(Proposition) - Constructor for class edu.cmu.tetrad.bayes.Proposition
Copies the info out of the old proposition into a new proposition for the new BayesIm.
Proposition(VariableSource, Proposition) - Constructor for class edu.cmu.tetrad.bayes.Proposition
Copies the info out of the old proposition into a new proposition for the new BayesIm.
ProximalGradient - Class in edu.pitt.csb.mgm
Implementation of Nesterov's 83 method as described in Beck and Teboulle, 2009 aka Fast Iterative Shrinkage Thresholding Algorithm
ProximalGradient() - Constructor for class edu.pitt.csb.mgm.ProximalGradient
Constructor using defaults from Becker et al 2011.
ProximalGradient(double, double, boolean) - Constructor for class edu.pitt.csb.mgm.ProximalGradient
Constructor, set parameters for a proximal gradient run
proximalOperator(double, DoubleMatrix1D) - Method in class edu.pitt.csb.mgm.Mgm
Applies proximal operator on the given input vector with a positive parameter.
pseudoinverse() - Method in class edu.cmu.tetrad.util.Matrix
Returns the Moore-Penrose pseudoinverse of the matrix.
purify(List<List<Node>>) - Method in interface edu.cmu.tetrad.search.utils.IPurify
purify.
purify(List<List<Node>>) - Method in class edu.cmu.tetrad.search.utils.PurifyScoreBased
purify.
purify(List<List<Node>>) - Method in class edu.cmu.tetrad.search.utils.PurifyTetradBased
purify.
purify(List<List<Integer>>) - Method in class edu.cmu.tetrad.search.utils.PurifySextadBased
purify.
Purify - Class in edu.cmu.tetrad.search.utils
Implements the Purify algorithm, which is a implementation of the automated purification methods described on CPS and the report "Learning Measurement Models" CMU-CALD-03-100.
Purify(CorrelationMatrix, double, BpcTestType, Clusters) - Constructor for class edu.cmu.tetrad.search.utils.Purify
****************************************************** INITIALIZATION o *******************************************************
Purify(DataSet, double, BpcTestType, Clusters) - Constructor for class edu.cmu.tetrad.search.utils.Purify
Constructor for Purify.
Purify(TetradTest, Clusters) - Constructor for class edu.cmu.tetrad.search.utils.Purify
Constructor for Purify.
PurifyScoreBased - Class in edu.cmu.tetrad.search.utils
Implements a score-based Purify method.
PurifyScoreBased(TetradTest, List<Set<String>>) - Constructor for class edu.cmu.tetrad.search.utils.PurifyScoreBased
Constructor for PurifyScoreBased.
PurifySextadBased - Class in edu.cmu.tetrad.search.utils
Implments a sextad-based Purify method.
PurifySextadBased(DeltaSextadTest, double) - Constructor for class edu.cmu.tetrad.search.utils.PurifySextadBased
Constructor for PurifySextadBased.
PurifyTetradBased - Class in edu.cmu.tetrad.search.utils
Implements a tetrad-based purify method.
PurifyTetradBased(TetradTest) - Constructor for class edu.cmu.tetrad.search.utils.PurifyTetradBased
Constructor for PurifyTetradBased.
put(String, ParamDescription) - Method in class edu.cmu.tetrad.util.ParamDescriptions
put.
putAll(Parameters) - Method in class edu.cmu.tetrad.util.Parameters
putAll.
putParameterValue(String, double) - Method in class edu.cmu.tetrad.sem.GeneralizedSemEstimator.MyContext
Puts a parameter value into the parameterValues map of the MyContext class.
putVariableValue(String, double) - Method in class edu.cmu.tetrad.sem.GeneralizedSemEstimator.MyContext
Puts a variable value into the variableValues map of the MyContext class.
PvalueDistanceToAlpha - Class in edu.cmu.tetrad.algcomparison.statistic
Estimates whether the p-values under the null are Uniform usign the Markov Checker.
PvalueDistanceToAlpha(double) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.PvalueDistanceToAlpha
Constructor for PvalueDistanceToAlpha.
pValuesAdP(Map<Pair<Node, Node>, Set<Double>>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Calculates the p-value using the Anderson-Darling test for a given set of p-values from an independence test.
PvalueUniformityUnderNull - Class in edu.cmu.tetrad.algcomparison.statistic
Estimates whether the p-values under the null are Uniform using the Markov Checker.
PvalueUniformityUnderNull(double) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.PvalueUniformityUnderNull
Constructor for PvalueUniformityUnderNull.

Q

quartile(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
quartile.
quartile(double[], int, int) - Static method in class edu.cmu.tetrad.util.StatUtils
quartile.
quartile(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
quartile.
quartile(long[], int, int) - Static method in class edu.cmu.tetrad.util.StatUtils
quartile.

R

R0R4Strategy - Interface in edu.cmu.tetrad.search.utils
The FCI orientation rules are almost entirely taken up with an examination of the FCI graph, but there are two rules that require looking at the distribution.
R0R4StrategyScoreBased - Class in edu.cmu.tetrad.search.utils
The FciOrientDataExaminationStrategyTestBased class implements the FciOrientDataExaminationStrategy interface and provides methods for checking unshielded colliders and determining orientations based on the Discriminating Path Rule.
R0R4StrategyTestBased - Class in edu.cmu.tetrad.search.utils
The FciOrientDataExaminationStrategyTestBased class implements the FciOrientDataExaminationStrategy interface and provides methods for checking unshielded colliders and determining orientations based on the Discriminating Path Rule.
R0R4StrategyTestBased(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Creates a new instance of FciOrientDataExaminationStrategyTestBased.
R0R4StrategyTestBased.BlockingType - Enum Class in edu.cmu.tetrad.search.utils
Enum representing the different types of blocking strategies.
R1 - Class in edu.cmu.tetrad.algcomparison.algorithm.pairwise
R1.
R1 - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The R1 rule.
R1() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R1
Constructor for R1.
R1(Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R1
Constructor for R1.
R1TimeLag - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The R1 Time Lag rule.
R2 - Class in edu.cmu.tetrad.algcomparison.algorithm.pairwise
R2.
R2 - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The R2 rule.
R2() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R2
Constructor for R2.
R2(Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R2
Constructor for R2.
R3 - Class in edu.cmu.tetrad.algcomparison.algorithm.pairwise
R3.
R3 - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The R3 rule.
R3() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R3
Constructor for R3.
R3(Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R3
Constructor for R3.
R5 - Enum constant in enum class edu.cmu.tetrad.search.utils.R5R9Dijkstra.Rule
The R5 rule.
R5R9Dijkstra - Class in edu.cmu.tetrad.search.utils
A modified implementation of Dijkstra's shortest path algorithm for the R5 and R9 rules from Zhang, J.
R5R9Dijkstra.DijkstraEdge - Class in edu.cmu.tetrad.search.utils
Represents a node in Dijkstra's algorithm.
R5R9Dijkstra.Graph - Class in edu.cmu.tetrad.search.utils
Represents a graph for Dijkstra's algorithm.
R5R9Dijkstra.Rule - Enum Class in edu.cmu.tetrad.search.utils
The rule that is being implemented, R5 or R9.
R9 - Enum constant in enum class edu.cmu.tetrad.search.utils.R5R9Dijkstra.Rule
The R9 rule.
random - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Random method
random - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
The random method.
RANDOM - Enum constant in enum class edu.cmu.tetrad.bayes.MlBayesIm.InitializationMethod
Represents a random initialization method.
RANDOM - Static variable in class edu.cmu.tetrad.bayes.MlBayesIm
Represents a constant value for a random number.
RANDOM_FOWARD_DAG - Static variable in class edu.cmu.tetrad.algcomparison.graph.GraphTypes
Constant RANDOM_FOWARD_DAG="Random Foward DAG (Fixed Average Degree"{trunked}
RANDOM_ONE_FACTOR_MIM - Static variable in class edu.cmu.tetrad.algcomparison.graph.GraphTypes
Constant RANDOM_ONE_FACTOR_MIM="Random One Factor MIM"
RANDOM_SELECTION_SIZE - Static variable in class edu.cmu.tetrad.util.Params
Constant RANDOM_SELECTION_SIZE="randomSelectionSize"
RANDOM_TWO_FACTOR_MIM - Static variable in class edu.cmu.tetrad.algcomparison.graph.GraphTypes
Constant RANDOM_TWO_FACTOR_MIM="Random Two Factor MIM"
randomBifactorModel(int, int, int, int, int, int) - Static method in class edu.cmu.tetrad.data.DataGraphUtils
First a random single factor model is created with the specified number of latent nodes and latent edges, and impurity structure.
randomClusters(int) - Static method in class edu.cmu.tetrad.cluster.KMeans
Constructs a new KMeansBatch, initializing the algorithm by randomly assigning each point in the data to one of the numCenters clusters, then calculating the centroid of each cluster.
randomCyclicGraph2(int, int, int) - Static method in class edu.cmu.tetrad.graph.RandomGraph
Makes a cyclic graph by repeatedly adding cycles of length of 3, 4, or 5 to the graph, then finally adding two cycles.
randomCyclicGraph3(int, int, int, double, double) - Static method in class edu.cmu.tetrad.graph.RandomGraph
Makes a cyclic graph by repeatedly adding cycles of length of 3, 4, or 5 to the graph, then finally adding two cycles.
randomDag(int, int, int, int, int, int, boolean) - Static method in class edu.cmu.tetrad.graph.RandomGraph
Generates a random Directed Acyclic Graph (DAG) with the specified parameters.
randomDag(List<Node>, int, int, int, int, int, boolean) - Static method in class edu.cmu.tetrad.graph.RandomGraph
Generates a random Directed Acyclic Graph (DAG).
RandomDistribution - Interface in edu.cmu.tetrad.study.gene.tetrad.gene.history
A distribution from which noise values are drawn.
RandomForward - Class in edu.cmu.tetrad.algcomparison.graph
Creates a random graph by adding forward edges.
RandomForward() - Constructor for class edu.cmu.tetrad.algcomparison.graph.RandomForward
Constructs a new instance of the RandomForward.
randomGraph(int, int, int, int, int, int, boolean) - Static method in class edu.cmu.tetrad.graph.RandomGraph
Generates a random graph based on the given parameters.
randomGraph(List<Node>, int, int, int, int, int, boolean) - Static method in class edu.cmu.tetrad.graph.RandomGraph
Generates a random graph based on the given parameters.
RandomGraph - Class in edu.cmu.tetrad.graph
The RandomGraph class provides methods for generating random graphs.
RandomGraph - Interface in edu.cmu.tetrad.algcomparison.graph
An interface to represent a random graph of some sort.
RandomGraph.UniformGraphGenerator - Class in edu.cmu.tetrad.graph
Generates random DAGs uniformly with certain classes of DAGs using variants of Markov chain algorithm by Malancon, Dutour, and Philippe.
randomGraphRandomForwardEdges(int, int, int, int, int, int, boolean) - Static method in class edu.cmu.tetrad.graph.RandomGraph
Generates a random graph with the given parameters and random forward edges.
randomGraphRandomForwardEdges(List<Node>, int, int, int, int, int, boolean) - Static method in class edu.cmu.tetrad.graph.RandomGraph
Generates a random graph with forward edges.
randomGraphRandomForwardEdges(List<Node>, int, int, int, int, int, boolean, boolean) - Static method in class edu.cmu.tetrad.graph.RandomGraph
Generates a random graph with forward edges.
randomGraphUniform(List<Node>, int, int, int, int, int, boolean, int) - Static method in class edu.cmu.tetrad.graph.RandomGraph
Generates a random graph using UniformGraphGenerator with the specified parameters.
randomize() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
Chooses a random function by flipping a coin for each value in table.
RANDOMIZE - Enum constant in enum class edu.cmu.tetrad.graph.NodeType
Constant RANDOMIZE
RANDOMIZE_COLUMNS - Static variable in class edu.cmu.tetrad.util.Params
Constant RANDOMIZE_COLUMNS="randomizeColumns"
randomizeGraph(LagGraph) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.GraphRandomizer
Randomizes the given lag graph--in other words, chooses random edges for the graph according to a particlar scheme (see instantiations).
randomizeIncompleteRows(int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Randomizes any row in the table for the given node index that has a Double.NaN value in it.
randomizeIncompleteRows(int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Randomizes any row in the table for the given node index that has a Double.NaN value in it.
randomizeIncompleteRows(int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Randomizes the incomplete rows in the specified node's table.
randomizeIncompleteRows(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Randomizes any row in the table for the given node index that has a Double.NaN value in it.
randomizeIncompleteRows(int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Randomizes any row in the table for the given node index that has a Double.NaN value in it.
randomizeRow(int, int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Assigns random probability values to the child values of this row that add to 1.
randomizeRow(int, int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Assigns random probability values to the child values of this row that add to 1.
randomizeRow(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Randomizes the values of a row in a table for a given node.
randomizeRow(int, int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Assigns random probability values to the child values of this row that add to 1.
randomizeRow(int, int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Assigns random probability values to the child values of this row that add to 1.
randomizeTable(int) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Randomizes every row in the table for the given node index.
randomizeTable(int) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Randomizes every row in the table for the given node index.
randomizeTable(int) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Randomizes the table for a given node.
randomizeTable(int) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Randomizes every row in the table for the given node index.
randomizeTable(int) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Randomizes every row in the table for the given node index.
randomMim(Graph, int, int, int, int, boolean) - Static method in class edu.cmu.tetrad.data.DataGraphUtils
randomMim.
randomPoints(int) - Static method in class edu.cmu.tetrad.cluster.KMeans
Constructs a new KMeansBatch, initializing the algorithm by picking numCeneters centers randomly from the data itself.
RandomSampler - Class in edu.cmu.tetrad.data
Provides a static method for sampling without replacement from a dataset to create a new dataset with a sample size supplied by the user.
RandomSampler() - Constructor for class edu.cmu.tetrad.data.RandomSampler
Constructs a new instance of the RandomSampler.
randomScaleFreeGraph(int, int, double, double, double, double) - Static method in class edu.cmu.tetrad.graph.RandomGraph
Generates a random scale-free graph.
randomSimulation(int) - Method in class edu.cmu.tetrad.simulation.GdistanceRandom
randomSimulation.
RandomSingleFactorMim - Class in edu.cmu.tetrad.algcomparison.graph
Creates a random graph by adding forward edges.
RandomSingleFactorMim() - Constructor for class edu.cmu.tetrad.algcomparison.graph.RandomSingleFactorMim
Constructs a new instance of the RandomSingleFactorMim.
randomSingleFactorModel(int, int, int, int, int, int) - Static method in class edu.cmu.tetrad.data.DataGraphUtils
randomSingleFactorModel.
RandomTwoFactorMim - Class in edu.cmu.tetrad.algcomparison.graph
Creates a random graph by adding forward edges.
RandomTwoFactorMim() - Constructor for class edu.cmu.tetrad.algcomparison.graph.RandomTwoFactorMim
Constructs a new instance of the RandomTwoFactorMim.
RandomUtil - Class in edu.cmu.tetrad.util
Provides a common random number generator to be used throughout Tetrad, to avoid problems that happen when random number generators are created more often than once per millisecond.
range(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
range.
range(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
range.
range(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
range.
range(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
range.
rank() - Method in class edu.cmu.tetrad.util.Matrix
rank.
rankCorrelation(double[], double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
rankCorrelation.
ranks(double[]) - Static method in class edu.cmu.tetrad.data.DataUtils
ranks.
RBExperiments - Class in edu.cmu.tetrad.study
RBExperiments class.
RBExperiments() - Constructor for class edu.cmu.tetrad.study.RBExperiments
Constructor for RBExperiments.
RC - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The RC rule.
RCIT_NUM_FEATURES - Static variable in class edu.cmu.tetrad.util.Params
Constant RCIT_NUM_FEATURES="rcitNumFeatures"
ReadControl - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker
ReadControl class.
ReadControl() - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ReadControl
Constructor for ReadControl.
readerToGraphJson(Reader) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
readerToGraphJson.
readerToGraphRuben(Reader) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
readerToGraphRuben.
readerToGraphTxt(Reader) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
readerToGraphTxt.
readerToGraphTxt(String) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
readerToGraphTxt.
readGraph(File) - Method in class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim
readGraph.
ReadIdeker - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker
ReadIdeker class.
ReadIdeker() - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.ideker.ReadIdeker
Constructor for ReadIdeker.
RealCovariance - Interface in edu.cmu.tetrad.stat.correlation
Jan 27, 2016 4:46:07 PM
RealCovarianceMatrix - Class in edu.cmu.tetrad.stat.correlation
Jan 27, 2016 5:35:01 PM
RealCovarianceMatrix(double[][]) - Constructor for class edu.cmu.tetrad.stat.correlation.RealCovarianceMatrix
Constructor for RealCovarianceMatrix.
RealCovarianceMatrixForkJoin - Class in edu.cmu.tetrad.stat.correlation
Jan 27, 2016 5:37:40 PM
RealCovarianceMatrixForkJoin(double[][], int) - Constructor for class edu.cmu.tetrad.stat.correlation.RealCovarianceMatrixForkJoin
Constructor for RealCovarianceMatrixForkJoin.
RealVariance - Interface in edu.cmu.tetrad.stat
Feb 9, 2016 3:13:19 PM
RealVarianceVector - Class in edu.cmu.tetrad.stat
Feb 9, 2016 3:14:08 PM
RealVarianceVector(double[][]) - Constructor for class edu.cmu.tetrad.stat.RealVarianceVector
Constructor for RealVarianceVector.
RealVarianceVectorForkJoin - Class in edu.cmu.tetrad.stat
Feb 9, 2016 3:15:29 PM
RealVarianceVectorForkJoin(double[][], int) - Constructor for class edu.cmu.tetrad.stat.RealVarianceVectorForkJoin
Constructor for RealVarianceVectorForkJoin.
recallUnshieldedTriples(Graph) - Method in class edu.cmu.tetrad.search.utils.AlmostCycleRemover
Recalls unshielded triples in the given graph.
recallUnshieldedTriples(Graph, Set<Triple>, Knowledge) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Recall unshielded triples in a given graph.
RECURSIVE - Enum constant in enum class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased.BlockingType
Recursive blocking.
RECURSIVE_MSEP - Enum constant in enum class edu.cmu.tetrad.search.ConditioningSetType
Conditioning on variables in the recursive order of a depth-first M-separation search.
REDIRECT - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move.Type
Redirect an edge.
RegexTokenizer - Class in edu.cmu.tetrad.data
Tokenizes the given input character sequence using the type of delimiter specified bythe given CPDAG.
RegexTokenizer(CharSequence, Pattern, char) - Constructor for class edu.cmu.tetrad.data.RegexTokenizer
Constructs a tokenizer for the given input line, using the given Pattern as delimiter.
regress(double[], double[][]) - Static method in class edu.cmu.tetrad.regression.RegressionDataset
regress.
regress(DiscreteVariable, List<Node>) - Method in class edu.cmu.tetrad.regression.LogisticRegression
x must be binary; regressors must be continuous or binary.
regress(Node, Node...) - Method in interface edu.cmu.tetrad.regression.Regression
Regresses target on the regressors, yielding a regression plane.
regress(Node, Node...) - Method in class edu.cmu.tetrad.regression.RegressionCovariance
regress.
regress(Node, Node...) - Method in class edu.cmu.tetrad.regression.RegressionDataset
regress.
regress(Node, List<Node>) - Method in interface edu.cmu.tetrad.regression.Regression
Regresses target on the regressors, yielding a regression plane.
regress(Node, List<Node>) - Method in class edu.cmu.tetrad.regression.RegressionCovariance
Regresses the given target on the given regressors, yielding a regression plane, in which coefficients are given for each regressor plus the constant (if means have been specified, that is, for the last), and se, t, and p values are given for each regressor.
regress(Node, List<Node>) - Method in class edu.cmu.tetrad.regression.RegressionDataset
Regresses the target on the given regressors.
Regression - Interface in edu.cmu.tetrad.regression
Implements a multiple regression model, allowing data to be specified either as a tabular data set or as a covariance matrix plus list of means.
RegressionCovariance - Class in edu.cmu.tetrad.regression
Implements a regression model from correlations--that is, from a correlation matrix, a list of standard deviations, and a list of means.
RegressionCovariance(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.regression.RegressionCovariance
Constructs a covariance-based regression model using the given covariance matrix, assuming that no means are specified.
RegressionDataset - Class in edu.cmu.tetrad.regression
Implements a regression model from tabular continuous data.
RegressionDataset(DataSet) - Constructor for class edu.cmu.tetrad.regression.RegressionDataset
Constructs a linear regression model for the given tabular data set.
RegressionDataset(Matrix, List<Node>) - Constructor for class edu.cmu.tetrad.regression.RegressionDataset
Constructor for RegressionDataset.
RegressionResult - Class in edu.cmu.tetrad.regression
Stores the various components of a regression result so they can be passed around together more easily.
RegressionResult(boolean, String[], int, double[], double[], double[], double[], double, double, double, Vector) - Constructor for class edu.cmu.tetrad.regression.RegressionResult
A result for a variety of regression algorithm.
RegressionUtils - Class in edu.cmu.tetrad.regression
Sundry utilities for regression.
RegressionUtils() - Constructor for class edu.cmu.tetrad.regression.RegressionUtils
Constructs a new instance of the RegressionUtils.
REGULAR - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.FasType
Regular FAS.
ReidentifyVariables - Class in edu.cmu.tetrad.sem
Utility for reidentifying variables for multiple indicator structure searches.
ReidentifyVariables() - Constructor for class edu.cmu.tetrad.sem.ReidentifyVariables
Constructs a new instance of the ReidentifyVariables.
reidentifyVariables1(List<List<Node>>, Graph) - Static method in class edu.cmu.tetrad.sem.ReidentifyVariables
reidentifyVariables1.
reidentifyVariables2(List<List<Node>>, Graph, DataSet) - Static method in class edu.cmu.tetrad.sem.ReidentifyVariables
reidentifyVariables2.
remove() - Method in class edu.cmu.tetrad.util.CombinationIterator
remove.
remove(int) - Method in class edu.cmu.tetrad.data.DataModelList
remove(IndependenceFact) - Method in class edu.cmu.tetrad.data.IndependenceFacts
remove.
remove(String) - Method in class edu.cmu.tetrad.util.Parameters
Removes the specified parameter from the list of parameters.
REMOVE - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move.Type
Remove an edge.
REMOVE_ALMOST_CYCLES - Static variable in class edu.cmu.tetrad.util.Params
Constant REMOVE_ALMOST_CYCLES="removeAlmostCycles"
REMOVE_COLLIDER - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move.Type
Remove a collider.
REMOVE_EFFECT_NODES - Static variable in class edu.cmu.tetrad.util.Params
Constant REMOVE_EFFECT_NODES="removeEffectNodes"
removeAlmostCycles(Graph) - Method in class edu.cmu.tetrad.search.utils.AlmostCycleRemover
Removes almost cycles from the Graph.
removeAlmostCycles(Graph, Set<Triple>, Set<Triple>, FciOrient, Knowledge, boolean) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Removes almost cycles from a graph.
removeAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Removes an ambiguous triple from the list of ambiguous triples.
removeAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
removeAmbiguousTriple.
removeAmbiguousTriple(Node, Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
removeAmbiguousTriple.
removeAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
removeAmbiguousTriple.
removeAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
removeAmbiguousTriple.
removeAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Removes an ambiguous triple from the collection.
removeAmbiguousTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Underlines
removeAmbiguousTriple.
removeAttribute(String) - Method in class edu.cmu.tetrad.data.ContinuousVariable
removeAttribute.
removeAttribute(String) - Method in class edu.cmu.tetrad.data.DiscreteVariable
removeAttribute.
removeAttribute(String) - Method in class edu.cmu.tetrad.graph.Dag
Removes an attribute from the graph.
removeAttribute(String) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
removeAttribute.
removeAttribute(String) - Method in interface edu.cmu.tetrad.graph.Graph
removeAttribute.
removeAttribute(String) - Method in class edu.cmu.tetrad.graph.GraphNode
removeAttribute.
removeAttribute(String) - Method in class edu.cmu.tetrad.graph.LagGraph
removeAttribute.
removeAttribute(String) - Method in interface edu.cmu.tetrad.graph.Node
removeAttribute.
removeAttribute(String) - Method in class edu.cmu.tetrad.graph.SemGraph
removeAttribute.
removeAttribute(String) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Removes the attribute with the specified key from the object.
removeBidirectedOrientations(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
removeBidirectedOrientations.
removeByPossibleMsep(IndependenceTest, SepsetMap) - Method in class edu.cmu.tetrad.graph.Paths
Remove edges by the possible m-separation rule.
removeCategory(int, int) - Method in class edu.cmu.tetrad.bayes.Proposition
removeCategory.
removeCols(int[]) - Method in class edu.cmu.tetrad.data.BoxDataSet
Removes the given columns from the data set.
removeCols(int[]) - Method in interface edu.cmu.tetrad.data.DataSet
Removes the given columns from the data set.
removeCols(int[]) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Removes the given columns from the data set.
removeColumn(int) - Method in class edu.cmu.tetrad.data.BoxDataSet
Removes the variable (and data) at the given index.
removeColumn(int) - Method in interface edu.cmu.tetrad.data.DataSet
Removes the variable (and data) at the given index.
removeColumn(int) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Removes the variable (and data) at the given index.
removeColumn(Node) - Method in class edu.cmu.tetrad.data.BoxDataSet
Removes the given variable, along with all of its data.
removeColumn(Node) - Method in interface edu.cmu.tetrad.data.DataSet
Removes the given variable, along with all of its data.
removeColumn(Node) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Removes the given variable, along with all of its data.
removeConditioningVariable(String) - Method in class edu.cmu.tetrad.data.Histogram
Removes a conditioning variable.
removeConstantColumns(DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
removeConstantColumns.
removeCycles(Graph) - Method in class edu.cmu.tetrad.search.utils.AlmostCycleRemover
Removes cycles from the Graph.
removeCycles(Set<Triple>, FciOrient, Graph, Knowledge, boolean) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Removes cycles from the given graph using the Fast Causal Inference (FCI) algorithm.
removeDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Removes a dotted underline triple from the set of triples.
removeDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
removeDottedUnderlineTriple.
removeDottedUnderlineTriple(Node, Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
removeDottedUnderlineTriple.
removeDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
removeDottedUnderlineTriple.
removeDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
removeDottedUnderlineTriple.
removeDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Removes a triple of nodes from the set of dottedUnderLineTriples.
removeDottedUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Underlines
removeDottedUnderlineTriple.
removeEdge(Edge) - Method in class edu.cmu.tetrad.graph.Dag
Removes a given edge from the graph.
removeEdge(Edge) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Removes the given edge from the graph.
removeEdge(Edge) - Method in interface edu.cmu.tetrad.graph.Graph
Removes the given edge from the graph.
removeEdge(Edge) - Method in class edu.cmu.tetrad.graph.LagGraph
Removes the given edge from the graph.
removeEdge(Edge) - Method in class edu.cmu.tetrad.graph.SemGraph
Removes the given edge from the graph.
removeEdge(Edge) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Removes an edge from the graph.
removeEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Removes the edge between two nodes in the graph.
removeEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Removes an edge between two given nodes.
removeEdge(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Removes an edge between two given nodes.
removeEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Removes an edge between two given nodes.
removeEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Removes an edge between two given nodes.
removeEdge(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Removes the edge between two given nodes.
removeEdge(String, LaggedFactor) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Removes the lagged factor from the list of lagged factors associated with the given factor.
removeEdge(String, LaggedFactor) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Removes the lagged factor from the list of lagged factors associated with the given factor.
removeEdge(String, LaggedFactor) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Removes the lagged factor from the list of lagged factors associated with the given factor.
removeEdge(String, LaggedFactor) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Removes the lagged factor from the list of lagged factors associated with the given factor.
removeEdges(Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Removes an edge between two nodes.
removeEdges(Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Removes all edges connecting node A to node B.
removeEdges(Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
Removes all edges connecting node A to node B.
removeEdges(Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Removes all edges connecting node A to node B.
removeEdges(Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Removes all edges connecting node A to node B.
removeEdges(Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Removes edges between two nodes.
removeEdges(Collection<Edge>) - Method in class edu.cmu.tetrad.graph.Dag
Removes the given edges from the graph.
removeEdges(Collection<Edge>) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Iterates through the list and removes any permissible edges found.
removeEdges(Collection<Edge>) - Method in interface edu.cmu.tetrad.graph.Graph
Iterates through the list and removes any permissible edges found.
removeEdges(Collection<Edge>) - Method in class edu.cmu.tetrad.graph.LagGraph
Iterates through the list and removes any permissible edges found.
removeEdges(Collection<Edge>) - Method in class edu.cmu.tetrad.graph.SemGraph
Iterates through the list and removes any permissible edges found.
removeEdges(Collection<Edge>) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Removes the specified collection of edges from the graph.
removeFactor(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Removes a factor from the graph.
removeFactor(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Removes a factor from the graph.
removeFactor(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Removes a factor from the graph.
removeFactor(String) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Removes a factor from the graph.
removeForbidden(String, String) - Method in class edu.cmu.tetrad.data.Knowledge
Marks the edge var1 --> var2 as not forbid.
removeFromClusters(String) - Method in class edu.cmu.tetrad.data.Clusters
Removes the given variable from the clusters.
removeFromTiers(String) - Method in class edu.cmu.tetrad.data.Knowledge
Removes the given variable by name or search string from all tiers.
removeHighLagEdges(int) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
removeHighLagEdges.
removeKnowledgeGroup(int) - Method in class edu.cmu.tetrad.data.Knowledge
Removes the knowledge group at the given index.
removeLatent(Node) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch.LatentStructure
removeLatent.
removeNaN(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
removeNaN.
removeNextOutputStream() - Method in class edu.cmu.tetrad.util.TetradLogger
removeNextOutputStream.
removeNode(Node) - Method in class edu.cmu.tetrad.graph.Dag
Removes the specified node from the graph.
removeNode(Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Removes a node from the graph.
removeNode(Node) - Method in interface edu.cmu.tetrad.graph.Graph
Removes a node from the graph.
removeNode(Node) - Method in class edu.cmu.tetrad.graph.LagGraph
Removes a node from the graph.
removeNode(Node) - Method in class edu.cmu.tetrad.graph.SemGraph
Removes a node from the graph.
removeNode(Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Removes the given node from the graph.
removeNodes(List<Node>) - Method in class edu.cmu.tetrad.graph.Dag
Removes the specified nodes from the graph.
removeNodes(List<Node>) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Iterates through the list and removes any permissible nodes found.
removeNodes(List<Node>) - Method in interface edu.cmu.tetrad.graph.Graph
Iterates through the list and removes any permissible nodes found.
removeNodes(List<Node>) - Method in class edu.cmu.tetrad.graph.LagGraph
Iterates through the list and removes any permissible nodes found.
removeNodes(List<Node>) - Method in class edu.cmu.tetrad.graph.SemGraph
Iterates through the list and removes any permissible nodes found.
removeNodes(List<Node>) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Removes the specified nodes from the graph.
removeNonSkeletonEdges(Graph, Knowledge) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Removes non-skeleton edges from the given graph based on the provided knowledge.
removeObserver(ModelObserver) - Method in class edu.cmu.tetrad.search.MarkovCheck
Removes the specified observer from the list of observers.
removeOutputStream(OutputStream) - Method in class edu.cmu.tetrad.util.TetradLogger
Removes the given stream from the logger.
removeProperty(Edge.Property) - Method in class edu.cmu.tetrad.graph.EdgeTypeProbability
removeProperty.
removePropertyChangeListener(PropertyChangeListener) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Unregisters a listener for events concerning the lag graph.
removeRandomColumns(DataSet, double) - Static method in class edu.cmu.tetrad.data.DataTransforms
removeRandomColumns.
removeRequired(String, String) - Method in class edu.cmu.tetrad.data.Knowledge
Marks the edge var1 --> var2 as not required.
removeRows(int[]) - Method in class edu.cmu.tetrad.data.BoxDataSet
Removes the specified rows from the dataBox, updates the selection, multipliers, and knowledge accordingly.
removeRows(int[]) - Method in interface edu.cmu.tetrad.data.DataSet
Removes the given rows from the data set.
removeRows(int[]) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Removes the given rows from the data set.
removeSimilarEdges(Node, Node) - Method in class edu.cmu.tetrad.search.SvarFges
Removes similar edges between two nodes.
removeTetradLoggerListener(TetradLoggerListener) - Method in class edu.cmu.tetrad.util.TetradLogger
Removes a TetradLoggerListener from the TetradLogger.
removeTriplesNotInGraph() - Method in class edu.cmu.tetrad.graph.Dag
Removes triples from the graph that contain nodes not present in the graph or are not adjacent to each other.
removeTriplesNotInGraph() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
removeTriplesNotInGraph.
removeTriplesNotInGraph() - Method in interface edu.cmu.tetrad.graph.Graph
removeTriplesNotInGraph.
removeTriplesNotInGraph() - Method in class edu.cmu.tetrad.graph.LagGraph
removeTriplesNotInGraph.
removeTriplesNotInGraph() - Method in class edu.cmu.tetrad.graph.SemGraph
removeTriplesNotInGraph.
removeTriplesNotInGraph() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Removes triples from the object's internal lists if any of the nodes in the triple is not present in the graph, or if any of the nodes are not adjacent to each other in the graph.
removeTriplesNotInGraph() - Method in class edu.cmu.tetrad.graph.Underlines
removeTriplesNotInGraph.
removeUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Dag
Removes an underline triple from the list of underline triples.
removeUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
removeUnderlineTriple.
removeUnderlineTriple(Node, Node, Node) - Method in interface edu.cmu.tetrad.graph.Graph
removeUnderlineTriple.
removeUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.LagGraph
removeUnderlineTriple.
removeUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.SemGraph
removeUnderlineTriple.
removeUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Removes the specified triple (x, y, z) from the list of underline triples.
removeUnderlineTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.graph.Underlines
removeUnderlineTriple.
removeVariables(List<String>) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Removes variables from the covariance matrix, retaining only the variables specified in the provided list.
removeVariables(List<String>) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Removes variables from the covariance matrix, retaining only the variables specified in the provided list.
removeVariables(List<String>) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Removes variables from the covariance matrix, retaining only the variables specified in the provided list.
removeVariables(List<String>) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Removes variables from the covariance matrix, retaining only the variables specified in the provided list.
removeZeroEdges(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
removeZeroEdges.
renameFactor(String, String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Renames a factor, changing all occurances of the old name to the new one
renameFactor(String, String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Renames a factor, changing all occurances of the old name to the new one
renameFactor(String, String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Renames a factor, changing all occurances of the old name to the new one
renameFactor(String, String) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Renames a factor, changing all occurances of the old name to the new one
render(BayesIm) - Static method in class edu.cmu.tetrad.bayes.BayesBifRenderer
Renders the given BayesIm object as a Bayesian network in the BIF (Bayesian Interchange Format) format.
reorientAllWith(Endpoint) - Method in class edu.cmu.tetrad.graph.Dag
Reorients all edges in a Directed Acyclic Graph (DAG) with a single endpoint type.
reorientAllWith(Endpoint) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Reorients all edges in the graph with the given endpoint.
reorientAllWith(Endpoint) - Method in interface edu.cmu.tetrad.graph.Graph
Reorients all edges in the graph with the given endpoint.
reorientAllWith(Endpoint) - Method in class edu.cmu.tetrad.graph.LagGraph
Reorients all edges in the graph with the given endpoint.
reorientAllWith(Endpoint) - Method in class edu.cmu.tetrad.graph.SemGraph
Reorients all edges in the graph with the given endpoint.
reorientAllWith(Endpoint) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Reorients all edges in the graph to point towards the specified endpoint.
reorientWithCircles(Graph, boolean) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Reorients all edges in a Graph as o-o.
replaceMissingWithRandom(DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
replaceMissingWithRandom.
replaceNodes(Graph, List<Node>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts the given graph, originalGraph, to use the new variables (with the same names as the old).
replaceNodes(List<Node>, Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts the given list of nodes, originalNodes, to use the replacement nodes for them by the same name in the given graph.
replaceNodes(List<Node>, List<Node>) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts the given list of nodes, originalNodes, to use the new variables (with the same names as the old).
repmat(double[][], int) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Make a n repeat copy of the rows and columns of the matrix mat.
repmat(double[][], int, int) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Make a repeat copy of matrix mat.
REQUIRED - Static variable in class edu.cmu.tetrad.data.KnowledgeGroup
The types of groups (Can an enum be used instead?)
requiredEdgesIterator() - Method in class edu.cmu.tetrad.data.Knowledge
Iterator over the KnowledgeEdge's representing required edges.
requiredViolations(Graph, Knowledge) - Static method in class edu.cmu.tetrad.search.CheckKnowledge
Returns a sorted list of edges that are required by knowledge but which do not appear in the graph.
requiresIndependenceTest(Class) - Method in class edu.cmu.tetrad.annotation.AlgorithmAnnotations
Checks if the algorithm requires independence test.
requiresScore(Class) - Method in class edu.cmu.tetrad.annotation.AlgorithmAnnotations
Checks if the algorithm requires a score.
RESAMPLING_ENSEMBLE - Static variable in class edu.cmu.tetrad.util.Params
Constant RESAMPLING_ENSEMBLE="resamplingEnsemble"
RESAMPLING_WITH_REPLACEMENT - Static variable in class edu.cmu.tetrad.util.Params
Constant RESAMPLING_WITH_REPLACEMENT="resamplingWithReplacement"
ResamplingEdgeEnsemble - Enum Class in edu.pitt.dbmi.algo.resampling
Sep 12, 2018 4:07:46 PM
reseedRandomGenerator(long) - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Reseeds the random number generator used by the empirical cumulative distribution function (CDF).
reset() - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
reset.
reset() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Resets the history initialization array to that a new data set can be generated.
reset() - Method in class edu.cmu.tetrad.util.TetradLogger
Resets the logger by removing any configuration info set with setTetradLoggerConfig.
resetCache() - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
resetCache.
resetErrorPositions() - Method in class edu.cmu.tetrad.graph.SemGraph
resetErrorPositions.
resetMag() - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Sets the MAG to null.
resetMag() - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Sets the MAG to null.
resetMag() - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Sets the MAG to null.
resetOrder() - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Sets the order ot null.
resetOrder() - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Sets the order ot null.
resetOrder() - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Sets the order ot null.
residuals(DataSet, Graph) - Static method in class edu.cmu.tetrad.regression.RegressionUtils
residuals.
resolveSepsets(List<SepsetMapDci>, List<IndependenceTest>, ResolveSepsetsDci.Method, SepsetMapDci, SepsetMapDci) - Static method in class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Resolves all inconsistencies between sepsets using a paricular method.
ResolveSepsets - Class in edu.cmu.tetrad.search.utils
Provides some utilities for resolving inconsistencies that arise between sepsets learned for overlapping datasets.
ResolveSepsets() - Constructor for class edu.cmu.tetrad.search.utils.ResolveSepsets
The method to use for resolving sepsets
ResolveSepsets.Method - Enum Class in edu.cmu.tetrad.search.utils
Gives the method to be used to resolve sepsets when they conflict.
ResolveSepsetsDci - Class in edu.cmu.tetrad.search.work_in_progress
Utilities for resolving inconsistencies that arise between sepsets learned for overlapping datasets.
ResolveSepsetsDci() - Constructor for class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci
Resolves the separation sets using the Decision Component Interface (DCI) algorithm.
ResolveSepsetsDci.Method - Enum Class in edu.cmu.tetrad.search.work_in_progress
A method for combining p values.
RESTRICTED_BOSS - Enum constant in enum class edu.cmu.tetrad.search.Cstar.CpdagAlgorithm
The RESTRICTED_BOSS algorithm.
RestrictedBoss - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
BOSS-DC (Best Order Score Search Divide and Conquer)
RestrictedBoss() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.RestrictedBoss
Constructor for RestrictedBoss.
RestrictedBoss(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.RestrictedBoss
Constructor for RestrictedBoss.
restrictToMeasured(DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
restrictToMeasured.
restrictToMeasured(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Removes all latent nodes from the graph and returns the modified graph.
restrictToProposition(Proposition) - Method in class edu.cmu.tetrad.bayes.Proposition
Restricts this proposition to the categories for each variable that are true in the given proposition.
Result(double, double, int, boolean) - Constructor for class edu.cmu.tetrad.search.test.ChiSquareTest.Result
Constructs a new g square result using the given parameters.
Result(double, double, int, boolean, boolean) - Constructor for class edu.cmu.tetrad.search.test.ChiSquareTest.Result
Constructs a new g square result using the given parameters.
Result(Matrix) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Glasso.Result
Constructor for Result.
Result(String, List<String>, double[], double[], int, int, int, double[], double[], double[], double, double, double, double) - Constructor for class edu.cmu.tetrad.regression.LogisticRegression.Result
Constructs a new LinRegrResult.
resultGraph() - Method in class edu.cmu.tetrad.search.PcMb
Returns the result graph.
retainValues(SemIm, SemGraph) - Static method in class edu.cmu.tetrad.sem.SemIm
Constructs a new SEM IM with the given graph, retaining parameter values from semIm for nodes of the same name and edges connecting nodes of the same names.
ReturnsBootstrapGraphs - Interface in edu.cmu.tetrad.algcomparison.algorithm
ReturnsBootstrapGraphs interface.
RevealEvaluator - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal
Provides the methods for computing mutual information between expression levels between genes and, for a given gene, between points in time determined by a lag value.
RevealEvaluator - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
Provides the methods for computing mutual information between expression levels between genes and, for a given gene, between points in time determined by a lag value.
RevealEvaluator(int[][]) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealEvaluator
Constructor for RevealEvaluator.
RevealEvaluator(int[][]) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealEvaluator
Constructor for RevealEvaluator.
RevealOutputGraph - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu
RevealOutputGraph class.
RevealOutputGraph - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal
RevealOutputGraph class.
RevealOutputGraph - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
RevealOutputGraph class.
RevealOutputGraph(int, int[][], int[][], String[], String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.RevealOutputGraph
Constructor for RevealOutputGraph.
RevealOutputGraph(int, int[][], int[][], String[], String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealOutputGraph
Constructor for RevealOutputGraph.
RevealOutputGraph(int, int[][], int[][], String[], String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealOutputGraph
Constructor for RevealOutputGraph.
RevealSearch - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal
This class contains as a member variable (cases) the time series data stored in an int array of microarray measurements.
RevealSearch - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
This class contains as a member variable (cases) the time series data stored in an int array of microarray measurements.
RevealSearch(int[][], String[]) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.RevealSearch
Constructor for RevealSearch.
RevealSearch(int[][], String[]) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.RevealSearch
Constructor for RevealSearch.
reverse() - Method in class edu.cmu.tetrad.graph.Edge
reverse.
revertSeed(long) - Method in class edu.cmu.tetrad.util.RandomUtil
revertSeed.
Rfci - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
RFCI.
Rfci - Class in edu.cmu.tetrad.search
Implements the Really Fast Causal Inference (RFCI) algorithm, which aims to do a correct inference of inferrable causal structure under the assumption that unmeasured common causes of variables in the data may exist.
Rfci() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci
Initializes a new instance of the Rfci class.
Rfci(IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci
Creates an instance of Rfci with the given IndependenceWrapper.
Rfci(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.Rfci
Constructs a new RFCI search for the given independence test and background knowledge.
Rfci(IndependenceTest, List<Node>) - Constructor for class edu.cmu.tetrad.search.Rfci
Constructs a new RFCI search for the given independence test and background knowledge and a list of variables to search over.
RFCI_PARAMETERS - Static variable in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci
Constant RFCI_PARAMETERS
RfciBsc - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
Runs RFCI-BSC, which is RFCI with bootstrap sampling of PAGs.
RfciBsc - Class in edu.pitt.dbmi.algo.bayesian.constraint.search
Dec 17, 2018 3:28:15 PM
RfciBsc() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.RfciBsc
Blank constructor.
RfciBsc(Rfci) - Constructor for class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Constructor for RfciBsc.
RIC - Enum constant in enum class edu.cmu.tetrad.search.score.GicScores.RuleType
The RIC rule.
RICc - Enum constant in enum class edu.cmu.tetrad.search.score.GicScores.RuleType
The RICc rule.
ricf(SemGraph, ICovarianceMatrix, double) - Method in class edu.cmu.tetrad.sem.Ricf
Calculates the Restricted Information Criterion Fusion (RICF) for a given SemGraph.
Ricf - Class in edu.cmu.tetrad.sem
Implements ICF as specified in Drton and Richardson (2003), Iterative Conditional Fitting for Gaussian Ancestral Graph Models, using hints from previous implementations by Drton in the ggm package in R and by Silva in the Purify class.
Ricf() - Constructor for class edu.cmu.tetrad.sem.Ricf
Represents the Ricf class.
Ricf.FitConGraphResult - Class in edu.cmu.tetrad.sem
The fit con graph result.
Ricf.RicfResult - Class in edu.cmu.tetrad.sem
RICF result.
ricf2(Graph, ICovarianceMatrix, double) - Method in class edu.cmu.tetrad.sem.Ricf
Same as above but takes a Graph instead of a SemGraph
RicfResult(DoubleMatrix2D, DoubleMatrix2D, DoubleMatrix2D, DoubleMatrix2D, int, double, ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.sem.Ricf.RicfResult
The result.
RIGHT_JUSTIFIED - Static variable in class edu.cmu.tetrad.util.TextTable
Set justification to this if the columns should be right justified.
robustSkew(double[], double[], boolean) - Static method in class edu.cmu.tetrad.search.FaskOrig
Calculates a left-right judgment using the robust skewness between two arrays of double values.
RocCalculator - Class in edu.cmu.tetrad.util
Calculates a ROC curve and AUC (area under curve) for a list of scored cases whose inclusion in category C is known.
RocCalculator(double[], boolean[], int) - Constructor for class edu.cmu.tetrad.util.RocCalculator
Constructs a calculator using the parameter information below.
rowCount() - Method in interface edu.pitt.isp.sverchkov.data.DataTable
rowCount.
rowCount() - Method in class edu.pitt.isp.sverchkov.data.DataTableImpl
rowCount.
RowsSettable - Interface in edu.cmu.tetrad.search.test
Interface for tests that can have their rows set on the fly.
RowSummingExactUpdater - Class in edu.cmu.tetrad.bayes
Performs updating operations on a BayesIm by summing over cells in the joint probability table for the BayesIm.
RowSummingExactUpdater(BayesIm) - Constructor for class edu.cmu.tetrad.bayes.RowSummingExactUpdater
Constructs a new updater for the given Bayes net.
RowSummingExactUpdater(BayesIm, Evidence) - Constructor for class edu.cmu.tetrad.bayes.RowSummingExactUpdater
Constructs a new updater for the given Bayes net.
RPAREN - Enum constant in enum class edu.cmu.tetrad.calculator.parser.Token
Right parenthesis.
Rskew - Class in edu.cmu.tetrad.algcomparison.algorithm.pairwise
RSkew.
Rskew() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Rskew
Constructor for Rskew.
Rskew(Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Rskew
Constructor for Rskew.
RSkew - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The RSkew rule.
RSKEW - Enum constant in enum class edu.cmu.tetrad.search.Fask.LeftRight
The robust skew rule from the Hyvarinen and Smith paper.
RSKEW - Enum constant in enum class edu.cmu.tetrad.search.FaskOrig.LeftRight
The robust skew rule from the Hyvarinen and Smith paper.
RskewE - Class in edu.cmu.tetrad.algcomparison.algorithm.pairwise
RSkewE.
RskewE() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.RskewE
Constructor for RskewE.
RskewE(Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.RskewE
Constructor for RskewE.
RSkewE - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The RSkewE rule.
ruleR0(Graph, Set<Triple>) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Orients unshielded colliders in the graph.
ruleR1(Node, Node, Node, Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
R1 If α ∗→ β o−−∗ γ, and α and γ are not adjacent, then orient the triple as α ∗→ β → γ.
ruleR10(Node, Node, Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
R10 Suppose α o→ γ, β → γ ← θ, p1 is an uncovered potentially directed (semidirected) path from α to β, and p2 is an uncovered p.d.
ruleR2(Node, Node, Node, Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
R2 If α → β ∗→ γ or α ∗→ β → γ, and α ∗−o γ, then orient α ∗−o γ as α ∗→ γ.
ruleR3(Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
R3 If α ∗→ β ←∗ γ, α ∗−o θ o−∗ γ, α and γ are not adjacent, and θ ∗−o β, then orient θ ∗−o β as θ ∗→ β.
ruleR4(Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
R4 If u = <θ ,...,α,β,γ> is a discriminating path between θ and γ for β, and β o−−∗ γ; then if β ∈ Sepset(θ,γ), orient β o−−∗ γ as β → γ; otherwise orient the triple <α,β,γ> as α ↔ β ↔ γ.
ruleR5(Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
R5 For every (remaining) α o−−o β, if there is an uncovered circle path p = <α,γ,...,θ,β> between α and β s.t.
ruleR6(Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
R6 If α —- β o−−∗ γ (α and γ may or may not be adjacent), then orient β o−−∗ γ as β −−∗ γ.
ruleR7(Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
R7 If α −−o β o−−∗ γ, and α, γ are not adjacent, then orient β o−−∗ γ as β −−∗ γ.
ruleR8(Node, Node, Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
R8 If α → β → γ or α−−◦β → γ, and α o→ γ, orient α o→ γ as α → γ.
ruleR9(Node, Node, Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
R9 If α o→ γ, and p = <α,β,θ,...,γ> is an uncovered potentialy directed path from α to γ such that γ and β are not adjacent, then orient α o→ γ as α → γ.
rulesR1R2cycle(Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Apply rules R1 and R2 in cycles for a given graph.
rulesR8R9R10(Graph) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Implements Zhang's rules R8, R9, R10, applies them over the graph once.
run(int) - Method in class edu.cmu.tetrad.simulation.HsimAutoC
run.
run(int) - Method in class edu.cmu.tetrad.simulation.HsimAutoRun
run.
run(int, double, int, double, int, int, boolean) - Static method in class edu.cmu.tetrad.simulation.HsimRobustCompare
run.
run(int, int) - Method in class edu.cmu.tetrad.simulation.HsimRepeatAC
run.
run(int, int) - Method in class edu.cmu.tetrad.simulation.HsimRepeatAutoRun
run.
run(String, String, char, String[], boolean) - Static method in class edu.cmu.tetrad.simulation.HsimRun
run.
run(List<Callable<T>>) - Method in class edu.cmu.tetrad.util.TaskRunner
Executes a list of tasks that implement Callable in parallel using multiple threads.
RunConfig - Class in edu.cmu.tetrad.algcomparison.examples
An example script to save out data files and graphs from a simulation.
RunConfig() - Constructor for class edu.cmu.tetrad.algcomparison.examples.RunConfig
Constructs a new instance of the Save.
RunKemmeren - Class in edu.cmu.tetrad.algcomparison.examples
RunKemmeren class.
RunKemmeren() - Constructor for class edu.cmu.tetrad.algcomparison.examples.RunKemmeren
Constructor for RunKemmeren.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Fofc
Runs the search algorithm and returns the resulting graph.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Ftfc
Runs the search algorithm to find a causal graph.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Dagma
Runs the DAGMA algorithm to search for a directed acyclic graph (DAG) in the given data model with the specified parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.DirectLingam
Runs the Direct LiNGAM search algorithm on the given data model with the specified parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Runs the Fask search algorithm on the given data model with the specified parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Runs the Fask search algorithm on the given data model with the specified parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingam
Searches for a graph structure based on the given data set and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingD
Runs a search on the provided data set using the given parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.mixed.Mgm
Runs the MGM search algorithm.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Runs the search algorithm using the given dataset and parameters and returns the resulting graph.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossDumb
Runs the search algorithm to find a graph structure based on a given data model and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPag
Runs the search algorithm to find a graph structure based on a given data model and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Ccd
Runs the CCD (Cyclic Causal Discovery) search algorithm on the given data set using the specified parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci
Runs the search algorithm to discover the causal graph.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci
Runs a search algorithm to find a graph based on the given data model and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax
Runs a search algorithm to discover the causal graph structure.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Runs the search algorithm to infer the causal graph given a dataset and specified parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Runs a search algorithm to find a graph structure based on a given data set and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
Runs the search algorithm to find a graph structure based on a given data model and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci
Runs the search algorithm using the given data set and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci
Runs the search algorithm on the given data model and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.RfciBsc
Runs a search algorithm using a given dataset and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Executes a search algorithm to infer the causal graph structure from a given data model
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarFci
Executes the search algorithm to find a graph structure that best fits the given dataset and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Runs a search algorithm on the given data set using the specified parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.other.FactorAnalysis
Executes a factor analysis search on the given data model using the provided parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.other.Glasso
Runs a search algorithm to create a graph representation of the data.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Eb
Runs a search algorithm to orient the edges in a graph using the given data and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.FaskPw
Runs the search algorithm using the given data model and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R1
Runs the search algorithm on the given data model with the provided parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R2
Runs the search algorithm using the provided data model and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R3
Runs the search algorithm to orient edges in the input graph using the provided data.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Rskew
Runs the search algorithm using the provided data model and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.RskewE
Runs a search algorithm to find the orientation of edges in a graph using the given data model and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Skew
Runs the search algorithm to orient edges in the input graph using the given data model and parameters.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.SkewE
Executes the SkewE search algorithm.
runSearch(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Tanh
Runs the search algorithm using the given data model and parameters.
runWithTimeout(Callable<T>, long, TimeUnit) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Runs the given task with the given timeout.

S

SAG - Enum constant in enum class edu.cmu.tetrad.search.Fofc.Algorithm
The SAG algorithm.
SAG - Enum constant in enum class edu.cmu.tetrad.search.Ftfc.Algorithm
The SAG algorithm.
SAG - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
SAG test, for FTFC.
sample() - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Returns a sample from the empirical cumulative distribution function (CDF).
sample(int) - Method in class edu.cmu.tetrad.sem.EmpiricalCdf
Returns a sample from the empirical cumulative distribution function (CDF).
sample(DataSet, int) - Method in class edu.cmu.tetrad.data.BootstrapSampler
This method takes a dataset and a sample size and creates a new dataset containing that number of samples by drawing with replacement from the original dataset.
sample(DataSet, int) - Static method in class edu.cmu.tetrad.data.RandomSampler
This method takes a dataset and a sample size and creates a new dataset containing that number of samples by drawing with replacement from the original dataset.
SAMPLE_SIZE - Static variable in class edu.cmu.tetrad.util.Params
Constant SAMPLE_SIZE="sampleSize"
SAMPLE_STYLE - Static variable in class edu.cmu.tetrad.util.Params
Constant SAMPLE_STYLE="sampleStyle"
SampleVcpc - Class in edu.cmu.tetrad.search.work_in_progress
Implements a conservative version of PC, in which the Markov condition is assumed but faithfulness is tested locally.
SampleVcpc(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Constructs a CPC algorithm that uses the given independence test as oracle.
SampleVcpcFast - Class in edu.cmu.tetrad.search.work_in_progress
Implements a conservative version of PC, in which the Markov condition is assumed but faithfulness is tested locally.
SampleVcpcFast(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Constructs a CPC algorithm that uses the given independence test as oracle.
Save - Class in edu.cmu.tetrad.algcomparison.examples
An example script to save out data files and graphs from a simulation.
Save() - Constructor for class edu.cmu.tetrad.algcomparison.examples.Save
Constructs a new instance of the Save.
SAVE_BOOTSTRAP_GRAPHS - Static variable in class edu.cmu.tetrad.util.Params
Constant SAVE_BOOTSTRAP_GRAPHS="saveBootstrapGraphs"
SAVE_LATENT_VARS - Static variable in class edu.cmu.tetrad.util.Params
Constant SAVE_LATENT_VARS="saveLatentVars"
saveCSV(DataTable<Attribute, Value>, File, boolean) - Static method in class edu.pitt.isp.sverchkov.data.DataTools
Saves a data table to a file.
SaveDGSimulations - Class in edu.cmu.tetrad.algcomparison.examples
An example script to save out data files and graphs from a simulation.
SaveDGSimulations() - Constructor for class edu.cmu.tetrad.algcomparison.examples.SaveDGSimulations
Constructs a new instance of the SaveDGSimulations.
saveGraph(Graph, File, boolean) - Static method in class edu.cmu.tetrad.graph.GraphSaveLoadUtils
saveGraph.
saveKnowledge(Knowledge, Writer) - Static method in class edu.cmu.tetrad.data.DataWriter
saveKnowledge.
saveToFiles(String, Simulation, Parameters) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Saves the simulation data to file in the specified data path.
saveToFiles(String, Simulation, Parameters) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
Saves simulationWrapper data.
saveToFilesSingleSimulation(String, Simulation, Parameters) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Saves the results of a single simulation to files.
scalarMult(double) - Method in class edu.cmu.tetrad.util.Matrix
scalarMult.
scalarMult(double) - Method in class edu.cmu.tetrad.util.Vector
scalarMult.
scalarProduct(double, double[]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
scalarProduct.
scalarProduct(double, double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Multiplies the given matrix through by the given scalar.
scale(DataSet, double) - Static method in class edu.cmu.tetrad.data.DataTransforms
Scales the continuous variables in the given DataSet to have values in the range [-1, 1].
scale(DataSet, double[]) - Static method in class edu.cmu.tetrad.data.DataTransforms
 
scale(Matrix) - Static method in class edu.cmu.tetrad.search.IcaLingD
Scales the given matrix M by diving each entry (i, j) by M(j, j)
SCALE_FREE_ALPHA - Static variable in class edu.cmu.tetrad.util.Params
Constant SCALE_FREE_ALPHA="scaleFreeAlpha"
SCALE_FREE_BETA - Static variable in class edu.cmu.tetrad.util.Params
Constant SCALE_FREE_BETA="scaleFreeBeta"
SCALE_FREE_DAG - Static variable in class edu.cmu.tetrad.algcomparison.graph.GraphTypes
Constant SCALE_FREE_DAG="Scale Free DAG (Bollobas et al.)"
SCALE_FREE_DELTA_IN - Static variable in class edu.cmu.tetrad.util.Params
Constant SCALE_FREE_DELTA_IN="scaleFreeDeltaIn"
SCALE_FREE_DELTA_OUT - Static variable in class edu.cmu.tetrad.util.Params
Constant SCALE_FREE_DELTA_OUT="scaleFreeDeltaOut"
ScaleFree - Class in edu.cmu.tetrad.algcomparison.graph
Returns a scale free graph.
ScaleFree() - Constructor for class edu.cmu.tetrad.algcomparison.graph.ScaleFree
Constructs a new instance of the ScaleFree.
SCALING_FACTOR - Static variable in class edu.cmu.tetrad.util.Params
Constant BANDWIDTH_ADJUSTMENT="scalingFactor"
score() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
score.
score(Graph) - Method in class edu.cmu.tetrad.sem.DagScorer
Scores the given DAG using the implemented algorithm.
score(Graph) - Method in interface edu.cmu.tetrad.sem.Scorer
score.
score(List<Node>) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Scores the given permutation.
Score - Interface in edu.cmu.tetrad.search.score
Interface for a score.
Score - Annotation Interface in edu.cmu.tetrad.annotation
Sep 1, 2017 10:51:13 AM
Score(Scorer) - Constructor for class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Score
Constructor for Score.
Score(Scorer) - Constructor for class edu.cmu.tetrad.search.work_in_progress.HbsmsGes.Score
Constructor for Score.
ScoreAnnotations - Class in edu.cmu.tetrad.annotation
Sep 26, 2017 1:14:01 AM
scoreDag(Graph) - Method in class edu.cmu.tetrad.search.Fges
Scores a Directed Acyclic Graph (DAG) based on its structure.
scoreDag(Graph) - Method in class edu.cmu.tetrad.search.FgesMb
Scores the given directed acyclic graph (DAG).
scoreDag(Graph) - Method in class edu.cmu.tetrad.search.SvarFges
Calculates the score of a Directed Acyclic Graph (DAG).
scoreDag(Graph) - Method in interface edu.cmu.tetrad.search.utils.DagScorer
scoreDag.
scoreDag(Graph) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
scoreDag.
scoreDag(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
scoreDag.
scoreDag(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Computes the score of a given directed acyclic graph (DAG).
scoreDag(Graph, DataModel, boolean) - Static method in class edu.cmu.tetrad.search.score.SemBicScorer
Scores the given DAG using the given data model, usimg a BIC score.
scoreDag(Graph, DataModel, double, boolean) - Static method in class edu.cmu.tetrad.search.score.SemBicScorer
Scores the given DAG using the given data model, usimg a BIC score.
scoreDag(Graph, Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Computes the score of a Directed Acyclic Graph (DAG) based on a given population graph.
ScoreDescriptions - Class in edu.cmu.tetrad.util
May 14, 2019 11:23:54 AM
ScoredGraph - Class in edu.cmu.tetrad.search.score
Stores a graph with a score for the graph.
ScoredGraph(Graph, Double) - Constructor for class edu.cmu.tetrad.search.score.ScoredGraph
Constructs a scored graph.
scoreGraph(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
scoreGraph.
scoreGraph(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
scoreGraph.
ScoreIndTest - Class in edu.cmu.tetrad.search.test
Gives a way of interpreting a score as an independence test.
ScoreIndTest(Score) - Constructor for class edu.cmu.tetrad.search.test.ScoreIndTest
Constructor for ScoreIndTest.
ScoreIndTest(Score, DataModel) - Constructor for class edu.cmu.tetrad.search.test.ScoreIndTest
Constructor for ScoreIndTest.
scoreLnGam(Node, Set<Node>, BayesPm, BayesIm) - Method in class edu.cmu.tetrad.bayes.BdeMetricCache
Computes the BDe score, using the logarithm of the gamma function, relative to the data, of the factor determined by a node and its parents.
Scorer - Interface in edu.cmu.tetrad.sem
Interface for a class that represents a scoring of a SEM model.
scoreRow(int, Matrix, List<List<Integer>>, List<List<Double>>) - Method in class edu.cmu.tetrad.search.Lofs
Calculates the score for a given row in a matrix using the specified parameters.
scoreTest() - Method in class edu.cmu.tetrad.bayes.FactoredBayesStructuralEM
scoreTest.
ScoreType - Enum Class in edu.cmu.tetrad.sem
Author : Jeremy Espino MD Created 1/12/18 2:05 PM
ScoreWrapper - Interface in edu.cmu.tetrad.algcomparison.score
Interface that algorithm must implement.
sd(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
sd.
sd(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
sd.
sd(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
sd.
sd(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
sd.
search() - Method in class edu.cmu.tetrad.search.BFci
Does the search and returns a PAG.
search() - Method in class edu.cmu.tetrad.search.BossLingam
Runs the search and returns the result graph.
search() - Method in class edu.cmu.tetrad.search.Bpc
Runs the search and returns the graph, or null if there is no model.
search() - Method in class edu.cmu.tetrad.search.Ccd
The search method assumes that the IndependenceTest provided to the constructor is a conditional independence oracle for the SEM (or Bayes network) which describes the causal structure of the population.
search() - Method in class edu.cmu.tetrad.search.Cfci
Performs the search and returns the PAG.
search() - Method in class edu.cmu.tetrad.search.Cpc
Runs CPC starting with a fully connected graph over all the variables in the domain of the independence test.
search() - Method in class edu.cmu.tetrad.search.Dagma
Performs a search algorithm to find a graph representation.
search() - Method in class edu.cmu.tetrad.search.DirectLingam
Performs the search.
search() - Method in class edu.cmu.tetrad.search.Fas
Performs a search to discover all adjacencies in the graph.
search() - Method in class edu.cmu.tetrad.search.Fasd
Discovers all adjacencies in data.
search() - Method in class edu.cmu.tetrad.search.Fask
Runs the search on the concatenated data, returning a graph, possibly cyclic, possibly with two-cycles.
search() - Method in class edu.cmu.tetrad.search.FaskOrig
Runs the search on the concatenated data, returning a graph, possibly cyclic, possibly with two-cycles.
search() - Method in class edu.cmu.tetrad.search.Fci
Performs a search using the FCI algorithm.
search() - Method in class edu.cmu.tetrad.search.FciMax
Performs the search and returns the PAG.
search() - Method in class edu.cmu.tetrad.search.Fges
Greedy equivalence search: Start from the empty graph, add edges till the model is significant.
search() - Method in class edu.cmu.tetrad.search.Fofc
Runs the search and returns a graph of clusters with the ir respective latent parents.
search() - Method in class edu.cmu.tetrad.search.Ftfc
Runs the search and returns a graph of clusters, each of which has two common latent parents.
search() - Method in class edu.cmu.tetrad.search.GFci
Runs the graph and returns the search PAG.
search() - Method in class edu.cmu.tetrad.search.GraspFci
Run the search and return s a PAG.
search() - Method in interface edu.cmu.tetrad.search.IGraphSearch
Runs the search and returns a graph.
search() - Method in class edu.cmu.tetrad.search.LvDumb
Run the search and return s a PAG.
search() - Method in class edu.cmu.tetrad.search.LvLite
Run the search and return s a PAG.
search() - Method in class edu.cmu.tetrad.search.Pc
Runs PC starting with a complete graph over all nodes of the given conditional independence test, using the given independence test and knowledge and returns the resultant graph.
search() - Method in class edu.cmu.tetrad.search.Pcd
Runs PC starting with a complete graph over all nodes of the given conditional independence test, using the given independence test and knowledge and returns the resultant graph.
search() - Method in class edu.cmu.tetrad.search.PcMb
Searches for the Markov blanket CPDAG for the given targets.
search() - Method in class edu.cmu.tetrad.search.PermutationSearch
Performs a search for a graph using the default options.
search() - Method in class edu.cmu.tetrad.search.Rfci
Runs the search and returns the RFCI PAG.
search() - Method in class edu.cmu.tetrad.search.SpFci
Runs the search and returns the discovered PAG.
search() - Method in class edu.cmu.tetrad.search.SvarFas
Discovers all adjacencies in data.
search() - Method in class edu.cmu.tetrad.search.SvarFci
Runs the search and returns the PAG.
search() - Method in class edu.cmu.tetrad.search.SvarFges
Greedy equivalence search: Start from the empty graph, add edges till the model is significant.
search() - Method in class edu.cmu.tetrad.search.SvarGfci
Runs the search and returns a PAG.
search() - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Greedy equivalence search: Start from the empty graph, add edges till model is significant.
search() - Method in class edu.cmu.tetrad.search.utils.PcCommon
Runs the search and returns the search graph.
search() - Method in class edu.cmu.tetrad.search.utils.PossibleMsepFci
Performs pairwise comparisons of each variable in the graph with the variables that have not already been checked.
search() - Method in class edu.cmu.tetrad.search.utils.Purify
****************************************************** SEARCH INTERFACE *******************************************************
search() - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
search.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.BpcTetradPurifyWashdown
Runs the search and returns a graph.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.Dci
Begins the DCI search procedure, described at each step
search() - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
search.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.FasDci
Discovers all adjacencies in data.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.FasFdr
Discovers all adjacencies in data.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.FasLofs
Runs the search on the concatenated data, returning a graph, possibly cyclic, possibly with two-cycles.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
search.
search() - Method in interface edu.cmu.tetrad.search.work_in_progress.Hbsms
search.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
search.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
search.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Executes the FCI algorithm using the provided independence test, score, and population graph, and returns the resulting graph with edges oriented according to the algorithm's rules.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.InverseCorrelation
search.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.Ion
Runs the ION search and returns a list of compatible graphs.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Greedy equivalence search: Start from the empty graph, add edges till the model is significant.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Runs PC starting with a complete graph over all nodes of the given conditional independence test, using the given independence test and knowledge and returns the resultant graph.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.Mmhc
Runs PC starting with a fully connected graph over all of the variables in the domain of the independence test.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
search.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
search.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.VcFas
Discovers all adjacencies in data.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
search.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
search.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
search.
search() - Method in class edu.cmu.tetrad.search.work_in_progress.Washdown
Runs the Washdown algorithm and return a graph.
search() - Method in class edu.pitt.csb.mgm.Mgm
Simple search command for GraphSearch implementation.
search() - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.PagSamplingRfci
Runs the search and returns a graph.
search() - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Runs the search and returns a graph.
search(boolean) - Method in class edu.cmu.tetrad.search.PermutationSearch
Performe the search and return a CPDAG.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.AbstractBootstrapAlgorithm
Runs the search.
search(DataModel, Parameters) - Method in interface edu.cmu.tetrad.algcomparison.algorithm.Algorithm
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Bpc
Runs the search algorithm to build a graph using the given data model and parameters.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.FirstInflection
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskLofsConcatenated
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FasLofs
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Searches for a graph using the given data set and parameters.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.SingleGraphAlg
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection
Runs the search.
search(DataModel, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.StARS
Runs the search.
search(DataSet) - Method in class edu.pitt.csb.stability.DataGraphSearch
search.
search(DataSet) - Method in class edu.pitt.csb.stability.SearchWrappers.FgesWrapper
Search method.
search(DataSet) - Method in class edu.pitt.csb.stability.SearchWrappers.MGMWrapper
Search method.
search(DataSet) - Method in class edu.pitt.csb.stability.SearchWrappers.PcStableWrapper
Search method.
search(IFas) - Method in class edu.cmu.tetrad.search.SvarFci
Runs the search using a particular implementation of FAS.
search(IFas, List<Node>) - Method in class edu.cmu.tetrad.search.Pcd
Searches for a graph using the given IFas instance and list of nodes.
search(IFas, List<Node>) - Method in class edu.cmu.tetrad.search.Rfci
Runs the search and returns the RFCI PAG.
search(IFas, Set<Node>) - Method in class edu.cmu.tetrad.search.Pc
Runs the search using a particular implementation of the fast adjacency search (FAS), over the given sublist of nodes.
search(Parameters) - Method in class edu.cmu.tetrad.search.work_in_progress.FaskVote
Does the search.
search(List<DataModel>, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Runs the search.
search(List<DataModel>, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskLofsConcatenated
Runs the search.
search(List<DataModel>, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Runs the search.
search(List<DataModel>, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Runs the search.
search(List<DataModel>, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Runs the search.
search(List<DataModel>, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Searches for a graph using the given data sets and parameters.
search(List<DataModel>, Parameters) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Runs the search.
search(List<DataModel>, Parameters) - Method in interface edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm
Runs the search.
search(List<Node>) - Method in class edu.cmu.tetrad.search.Fas
Discovers all adjacencies in data.
search(List<Node>) - Method in class edu.cmu.tetrad.search.FgesMb
Greedy equivalence search: Start from the empty graph, add edges till the model is significant.
search(List<Node>) - Method in class edu.cmu.tetrad.search.Pcd
Runs PC starting with a complete graph over the given list of nodes, using the given independence test and knowledge and returns the resultant graph.
search(List<Node>) - Method in class edu.cmu.tetrad.search.PcMb
Searches for the MB CPDAG for the given targets.
search(List<Node>) - Method in class edu.cmu.tetrad.search.Rfci
Searches of a specific sublist of nodes.
search(List<Node>) - Method in class edu.cmu.tetrad.search.utils.PcCommon
Runs the search over the given list of nodes only, returning the search graph.
search(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Runs PC starting with a commplete graph over the given list of nodes, using the given independence test and knowledge and returns the resultant graph.
search(List<List<Node>>, List<String>, ICovarianceMatrix) - Method in class edu.cmu.tetrad.search.Mimbuild
Does a Mimbuild search.
search(List<List<Node>>, List<String>, ICovarianceMatrix) - Method in class edu.cmu.tetrad.search.MimbuildTrek
Does the search and returns the graph.
search(Set<Node>) - Method in class edu.cmu.tetrad.search.Pc
Runs PC starting with a complete graph over the given list of nodes, using the given independence test and knowledge and returns the resultant graph.
search_for_Markov_blankets - Enum constant in enum class edu.cmu.tetrad.annotation.AlgType
If an algorithm searches for Markov blanekts.
search_for_structure_over_latents - Enum constant in enum class edu.cmu.tetrad.annotation.AlgType
If an algorithm searches for structure over latents.
searchDemixedData() - Method in class edu.cmu.tetrad.search.work_in_progress.MixtureModel
Perform an FGES search on each of the demixed data sets.
searchParams - Variable in class edu.pitt.csb.stability.DataGraphSearch
searchParams.
searchSuborder(List<Node>, List<Node>, Map<Node, GrowShrinkTree>) - Method in class edu.cmu.tetrad.search.Boss
Searches a suborder of the variables.
searchSuborder(List<Node>, List<Node>, Map<Node, GrowShrinkTree>) - Method in class edu.cmu.tetrad.search.Sp
Searches for the best suborder of nodes given a prefix and a suborder.
searchSuborder(List<Node>, List<Node>, Map<Node, GrowShrinkTree>) - Method in interface edu.cmu.tetrad.search.SuborderSearch
Searches the suborder.
SearchWrappers - Class in edu.pitt.csb.stability
Created by ajsedgewick on 9/4/15.
SearchWrappers.FgesWrapper - Class in edu.pitt.csb.stability
Wrapper for the Fges search algorithm.
SearchWrappers.MGMWrapper - Class in edu.pitt.csb.stability
Abstract class for search algorithm wrappers.
SearchWrappers.PcStableWrapper - Class in edu.pitt.csb.stability
Abstract class for search algorithm wrappers.
SEED - Static variable in class edu.cmu.tetrad.util.Params
Constant SEED="seed"
select(Node) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Selects a specified variable in the covariance matrix.
select(Node) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Selects a specified variable in the covariance matrix.
select(Node) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Selects a specified variable in the covariance matrix.
select(Node) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Selects a specified variable in the covariance matrix.
SELECTION - Enum constant in enum class edu.cmu.tetrad.graph.NodeType
Constant SELECTION
SELECTION_MIN_EFFECT - Static variable in class edu.cmu.tetrad.util.Params
Constant SELECTION_MIN_EFFECT="selectionMinEffect"
SelectionGenerator - Class in edu.cmu.tetrad.util
Generates (nonrecursively) all of the selections from a items, where a is a nonnegative integer.
SelectionGenerator(int) - Constructor for class edu.cmu.tetrad.util.SelectionGenerator
Constructs a new selection generator for a items.
SELF_LOOP_COEF - Static variable in class edu.cmu.tetrad.util.Params
Constant SELF_LOOP_COEF="selfLoopCoef"
SEM_BIC_RULE - Static variable in class edu.cmu.tetrad.util.Params
Constant SEM_BIC_RULE="semBicRule"
SEM_BIC_STRUCTURE_PRIOR - Static variable in class edu.cmu.tetrad.util.Params
Constant SEM_BIC_STRUCTURE_PRIOR="semBicStructurePrior"
SEM_GIC_RULE - Static variable in class edu.cmu.tetrad.util.Params
Constant SEM_GIC_RULE="semGicRule"
SemBic - Enum constant in enum class edu.cmu.tetrad.sem.ScoreType
The BIC score
SemBicDTest - Class in edu.cmu.tetrad.algcomparison.independence
The SemBicDTest class implements the IndependenceWrapper interface and represents a test for independence based on SEM BIC algorithm.
SemBicDTest() - Constructor for class edu.cmu.tetrad.algcomparison.independence.SemBicDTest
Constructs a new instance of the SEM BIC test.
SemBicScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for linear, Gaussian SEM BIC score.
SemBicScore - Class in edu.cmu.tetrad.search.score
Implements the linear, Gaussian BIC score, with a 'penalty discount' multiplier on the BIC penalty.
SemBicScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.SemBicScore
Constructs a new instance of the SemBicScore.
SemBicScore(DataSet, boolean) - Constructor for class edu.cmu.tetrad.search.score.SemBicScore
Constructs the score using a covariance matrix.
SemBicScore(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.search.score.SemBicScore
Constructs the score using a covariance matrix.
SemBicScore.CovAndCoefs - Record Class in edu.cmu.tetrad.search.score
Represents a covariance matrix and regression coefficients.
SemBicScore.RuleType - Enum Class in edu.cmu.tetrad.search.score
Gives two options for calculating the BIC score, one describe by Chickering and the other due to Nandy et al.
SemBicScoreDeterministic - Class in edu.cmu.tetrad.algcomparison.score
SemBicScoreDeterministic is a class that implements the ScoreWrapper interface.
SemBicScoreDeterministic - Class in edu.cmu.tetrad.search.work_in_progress
Implements the continuous BIC score for FGES.
SemBicScoreDeterministic() - Constructor for class edu.cmu.tetrad.algcomparison.score.SemBicScoreDeterministic
Constructs a new instance of the SemBicScoreDeterministic.
SemBicScoreDeterministic(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Constructs the score using a covariance matrix.
SemBicScorer - Class in edu.cmu.tetrad.search.score
Scores an entire DAG using the SemBicScore.
SemBicTest - Class in edu.cmu.tetrad.algcomparison.independence
 
SemBicTest() - Constructor for class edu.cmu.tetrad.algcomparison.independence.SemBicTest
Constructs a new instance of the SEM BIC test.
SemEstimator - Class in edu.cmu.tetrad.sem
Estimates a SemIm given a CovarianceMatrix and a SemPm.
SemEstimator(DataSet, SemPm) - Constructor for class edu.cmu.tetrad.sem.SemEstimator
Constructs a Sem Estimator that does default estimation.
SemEstimator(DataSet, SemPm, SemOptimizer) - Constructor for class edu.cmu.tetrad.sem.SemEstimator
Constructs a new SemEstimator that uses the specified optimizer.
SemEstimator(ICovarianceMatrix, SemPm) - Constructor for class edu.cmu.tetrad.sem.SemEstimator
Constructs a SEM estimator that does default estimation.
SemEstimator(ICovarianceMatrix, SemPm, SemOptimizer) - Constructor for class edu.cmu.tetrad.sem.SemEstimator
Constructs a new SemEstimator that uses the specified optimizer.
SemEstimatorGibbs - Class in edu.cmu.tetrad.sem
Implements the Gibbs sampler apporach to obtain samples of arbitrary size from the posterior distribution over the freeParameters of a SEM given a continuous dataset and a SemPm.
SemEstimatorGibbs(int, double, double, double, double, SemPm, SemIm, boolean) - Constructor for class edu.cmu.tetrad.sem.SemEstimatorGibbs
Constructor for SemEstimatorGibbs.
SemEstimatorGibbs(SemPm, SemIm, double[][], boolean, double, int) - Constructor for class edu.cmu.tetrad.sem.SemEstimatorGibbs
Constructor for SemEstimatorGibbs.
SemEstimatorGibbsParams - Class in edu.cmu.tetrad.sem
Stores the freeParameters for an instance of a SemEstimatorGibbs.
SemEvidence - Class in edu.cmu.tetrad.sem
Stores information for a SemIm about evidence we have for each variable as well as whether each variable has been manipulated.
SemEvidence(SemEvidence) - Constructor for class edu.cmu.tetrad.sem.SemEvidence
Constructor for SemEvidence.
SemEvidence(SemIm) - Constructor for class edu.cmu.tetrad.sem.SemEvidence
Constructs a container for evidence for the given Bayes IM.
SemGraph - Class in edu.cmu.tetrad.graph
Represents the graphical structure of a structural equation model.
SemGraph() - Constructor for class edu.cmu.tetrad.graph.SemGraph
Constructs a new, empty SemGraph.
SemGraph(Graph) - Constructor for class edu.cmu.tetrad.graph.SemGraph
Constructs a new SemGraph from the nodes and edges of the given graph.
SemGraph(SemGraph) - Constructor for class edu.cmu.tetrad.graph.SemGraph
Copy constructor.
SemidirectedPathF1 - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the F1 statistic for adjacencies.
SemidirectedPathF1() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPathF1
Constructs the statistic.
semidirectedPaths(Node, Node, int) - Method in class edu.cmu.tetrad.graph.Paths
Finds all semi-directed paths between two nodes up to a maximum length.
SemidirectedPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
SemidirectedPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPrecision
Constructs the statistic.
SemidirectedRecall - Class in edu.cmu.tetrad.algcomparison.statistic
A class implementing the Semidirected-Rec statistic.
SemidirectedRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.SemidirectedRecall
Constructs the statistic.
semigraphoid() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Checked whether the IM is a semigraphoid.
SemIm - Class in edu.cmu.tetrad.sem
Stores an instantiated structural equation model (SEM), with error covariance terms, possibly cyclic, suitable for estimation and simulation.
SemIm(SemIm) - Constructor for class edu.cmu.tetrad.sem.SemIm
Copy constructor.
SemIm(SemPm) - Constructor for class edu.cmu.tetrad.sem.SemIm
Constructs a new SEM IM from a SEM PM.
SemIm(SemPm, ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.sem.SemIm
Constructs a SEM model using the given SEM PM and sample covariance matrix.
SemIm(SemPm, SemIm, Parameters) - Constructor for class edu.cmu.tetrad.sem.SemIm
Constructs a new SEM IM from the given SEM PM, using the old SEM IM and params object to guide the choice of parameter values.
SemIm(SemPm, Parameters) - Constructor for class edu.cmu.tetrad.sem.SemIm
Constructs a new SEM IM from the given SEM PM, using the given params object to guide the choice of parameter values.
SemIm(SemPm, List<Node>, List<Node>, Matrix, double[]) - Constructor for class edu.cmu.tetrad.sem.SemIm
Constructor for SemIm.
SemManipulation - Class in edu.cmu.tetrad.sem
Stores information for a BayesIm about evidence we have for each variable as well as whether each variable has been manipulated.
SemManipulation(SemIm) - Constructor for class edu.cmu.tetrad.sem.SemManipulation
Constructs a container for evidence for the given Bayes IM.
SemManipulation(SemManipulation) - Constructor for class edu.cmu.tetrad.sem.SemManipulation
Constructor for SemManipulation.
SemOptimizer - Interface in edu.cmu.tetrad.sem
Interface for algorithm that optimize the fitting function of a SemIm model by adjusting its freeParameters in search of a global maximum.
SemOptimizerEm - Class in edu.cmu.tetrad.sem
Optimizes a DAG SEM with hidden variables using expectation-maximization.
SemOptimizerEm() - Constructor for class edu.cmu.tetrad.sem.SemOptimizerEm
Constructor for SemOptimizerEm.
SemOptimizerPowell - Class in edu.cmu.tetrad.sem
Optimizes a SEM using Powell's method from the Apache library.
SemOptimizerPowell() - Constructor for class edu.cmu.tetrad.sem.SemOptimizerPowell
Blank constructor.
SemOptimizerRegression - Class in edu.cmu.tetrad.sem
Optimizes a DAG SEM by regressing each varaible onto its parents using a linear regression.
SemOptimizerRegression() - Constructor for class edu.cmu.tetrad.sem.SemOptimizerRegression
Blank constructor.
SemOptimizerRicf - Class in edu.cmu.tetrad.sem
Optimizes a SEM using RICF (see that class).
SemOptimizerRicf() - Constructor for class edu.cmu.tetrad.sem.SemOptimizerRicf
Blank constructor.
SemOptimizerScattershot - Class in edu.cmu.tetrad.sem
Optimizes a SEM by randomly selecting points in cubes of decreasing size about a given point.
SemOptimizerScattershot() - Constructor for class edu.cmu.tetrad.sem.SemOptimizerScattershot
Blank constructor.
SemPm - Class in edu.cmu.tetrad.sem
Parametric model for Structural Equation Models.
SemPm(Graph) - Constructor for class edu.cmu.tetrad.sem.SemPm
Constructs a BayesPm from the given Graph, which must be convertible first into a ProtoSemGraph and then into a SemGraph.
SemPm(SemGraph) - Constructor for class edu.cmu.tetrad.sem.SemPm
Constructs a new SemPm from the given SemGraph.
SemPm(SemPm) - Constructor for class edu.cmu.tetrad.sem.SemPm
Copy constructor.
SemProposition - Class in edu.cmu.tetrad.sem
Represents propositions over the variables of a particular BayesIm describing and event of a fairly general sort--namely, conjunctions of propositions that particular variables take on values from a particular disjunctive list of categories.
SemProposition(SemIm) - Constructor for class edu.cmu.tetrad.sem.SemProposition
Creates a new Proposition which allows all values.
SemProposition(SemProposition) - Constructor for class edu.cmu.tetrad.sem.SemProposition
Creates a new SemProposition object by copying the values and semIm from the given proposition.
SemSimulation - Class in edu.cmu.tetrad.algcomparison.simulation
This class represents a Simulation using Structural Equation Modeling (SEM).
SemSimulation(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Constructs a SemSimulation object with the given RandomGraph object.
SemSimulation(SemIm) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Constructs a GeneralSemSimulation object with the given SemIm object.
SemSimulation(SemPm) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.SemSimulation
Initializes a SemSimulation with the given SemPm object.
SemStdErrorEstimator - Class in edu.cmu.tetrad.sem
Includes methods for estimating the standard errors of the freeParameters of an estimated SEM.
SemStdErrorEstimator() - Constructor for class edu.cmu.tetrad.sem.SemStdErrorEstimator
Blank constructor.
SemThenDiscretize - Class in edu.cmu.tetrad.algcomparison.simulation
SEM the discretize.
SemThenDiscretize(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
Constructor for SemThenDiscretize.
SemThenDiscretize(RandomGraph, DataType) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize
Constructor for SemThenDiscretize.
SemUpdater - Class in edu.cmu.tetrad.sem
Calculates updated structural equation models given evidence of the form X1=x1',...,The main task of such and algorithm is to calculate P(X = x' | evidence), where evidence takes the form of a Proposition over the variables in the Bayes net, possibly with additional information about which variables in the Bayes net have been manipulated.
SemUpdater(SemIm) - Constructor for class edu.cmu.tetrad.sem.SemUpdater
Constructor for SemUpdater.
SemXmlParser - Class in edu.cmu.tetrad.sem
This class takes an xml element representing a SEM im and converts it to a SemIM
SemXmlParser() - Constructor for class edu.cmu.tetrad.sem.SemXmlParser
This class represents a parser for SEM XML representation.
SemXmlRenderer - Class in edu.cmu.tetrad.sem
This class converts a SemIm into xml.
SEPSET_FINDER_METHOD - Static variable in class edu.cmu.tetrad.util.Params
Constant SEPSET_FINDER_METHOD="sepsetFinderMethod"
SepsetFinder - Class in edu.cmu.tetrad.search
This class provides methods for finding sepsets in a given graph.
SepsetFinder() - Constructor for class edu.cmu.tetrad.search.SepsetFinder
Private constructor to prevent instantiation.
SepsetMap - Class in edu.cmu.tetrad.search.utils
Stores a map from pairs of nodes to separating sets--that is, for each unordered pair of nodes {node1, node2} in a graph, stores a set of nodes conditional on which node1 and node2 are independent (where the nodes are considered as variables) or stores null if the pair was not judged to be independent.
SepsetMap() - Constructor for class edu.cmu.tetrad.search.utils.SepsetMap
Constructor.
SepsetMap(SepsetMap) - Constructor for class edu.cmu.tetrad.search.utils.SepsetMap
Copy constructor.
SepsetMapDci - Class in edu.cmu.tetrad.search.work_in_progress
This is the same as the usual SepsetMap described below, but also keeps up with the individual sets of conditioning nodes for d-separation relations for use with the Distributed Causal Inference (DCI) algorithm.
SepsetMapDci() - Constructor for class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
Constructor for SepsetMapDci.
SepsetMapDci(SepsetMapDci) - Constructor for class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
Constructor for SepsetMapDci.
SepsetProducer - Interface in edu.cmu.tetrad.search.utils
Provides a covenience interface for classes that can generate and keep track of sepsets.
SepsetsGreedy - Class in edu.cmu.tetrad.search.utils
Provides a SepsetProducer that selects the first sepset it comes to from among the extra sepsets or the adjacents of i or k, or null if none is found.
SepsetsGreedy(Graph, IndependenceTest, int) - Constructor for class edu.cmu.tetrad.search.utils.SepsetsGreedy
Constructor for Sepsets.
SepsetsMaxP - Class in edu.cmu.tetrad.search.utils
The class SepsetsMaxP implements the SepsetProducer interface and provides methods for generating sepsets based on a given graph and an independence test.
SepsetsMaxP(Graph, IndependenceTest, int) - Constructor for class edu.cmu.tetrad.search.utils.SepsetsMaxP
Constructs a SepsetsMaxP object with the given graph, independence test, and depth.
SepsetsMinP - Class in edu.cmu.tetrad.search.utils
The SepsetsMinP class is a concrete implementation of the SepsetProducer interface.
SepsetsMinP(Graph, IndependenceTest, int) - Constructor for class edu.cmu.tetrad.search.utils.SepsetsMinP
Initializes a new instance of the SepsetsMinP class.
SepsetsPossibleMsep - Class in edu.cmu.tetrad.search.utils
Provides a sepset producer using conditional independence tests to generate the Sepset map, for the case where possible msep sets are required.
SepsetsPossibleMsep(Graph, IndependenceTest, Knowledge, int, int) - Constructor for class edu.cmu.tetrad.search.utils.SepsetsPossibleMsep
Constructor for SepsetsPossibleMsep.
SepsetsSet - Class in edu.cmu.tetrad.search.utils
Provides a sepset producer using conditional independence tests to generate the Sepset map.
SepsetsSet(SepsetMap, IndependenceTest) - Constructor for class edu.cmu.tetrad.search.utils.SepsetsSet
Constructor for SepsetsSet.
SERIAL - Enum constant in enum class edu.cmu.tetrad.search.LvLite.ExtraEdgeRemovalStyle
Remove extra edges in serial.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.ApproximateUpdater
Returns a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.BayesImProbs
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.BayesPm
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.CptInvariantMarginalCalculator
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.Evidence
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.Identifiability
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.Manipulation
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.MlBayesIm
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.MlBayesImObs
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.Proposition
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.StoredCellProbs
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.calculator.expression.ConstantExpression
serializableInstance.
serializableInstance() - Static method in class edu.cmu.tetrad.calculator.expression.EvaluationExpression
serializableInstance.
serializableInstance() - Static method in enum class edu.cmu.tetrad.calculator.expression.ExpressionDescriptor.Position
serializableInstance.
serializableInstance() - Static method in class edu.cmu.tetrad.calculator.expression.VariableExpression
serializableInstance.
serializableInstance() - Static method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.BoxDataSet
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.ByteDataBox
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.Clusters
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.ContinuousDiscretizationSpec
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.ContinuousVariable
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.CorrelationMatrix
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.CovarianceMatrix
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.DataModelList
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.DelimiterType
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.DiscreteDiscretizationSpec
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.DiscreteVariable
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.DiscreteVariableType
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.DoubleDataBox
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.FloatDataBox
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.IndependenceFacts
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.IntDataBox
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.Knowledge
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.KnowledgeEdge
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.KnowledgeGroup
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.LongDataBox
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.MixedDataBox
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.NumberObjectDataSet
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.ShortDataBox
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.SplitCasesSpec
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.TimeSeriesData
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.VerticalDoubleDataBox
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.data.VerticalIntDataBox
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.graph.Dag
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.graph.Edge
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.graph.EdgeListGraph
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.graph.GraphNode
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.graph.IndependenceFact
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.graph.LagGraph
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.graph.SemGraph
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.graph.TimeLagGraph
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.graph.Triple
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.regression.LogisticRegression.Result
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.regression.LogisticRegression
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.regression.RegressionResult
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.search.score.ScoredGraph
Returns a serializable instance of this class.
serializableInstance() - Static method in class edu.cmu.tetrad.search.test.IndependenceResult
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in enum class edu.cmu.tetrad.search.utils.BpcAlgorithmType
Returns the serializable instance of the algorithm type.
serializableInstance() - Static method in enum class edu.cmu.tetrad.search.utils.BpcTestType
Returns the serializable instance of the test type.
serializableInstance() - Static method in class edu.cmu.tetrad.search.utils.DeltaSextadTest
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.search.utils.SepsetMap
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.search.utils.Sextad
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.search.work_in_progress.Sextad
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.DagScorer
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.Mapping
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.ParamConstraint
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.Parameter
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.ParameterPair
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemEstimator
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemEstimatorGibbsParams
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemEvidence
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemIm
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemManipulation
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemOptimizerEm
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemOptimizerPowell
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemOptimizerRegression
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemOptimizerRicf
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemOptimizerScattershot
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemPm
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemProposition
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.SemUpdater
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.StandardizedSemIm.ParameterRange
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.sem.StandardizedSemIm
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
serializableInstance.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraphParams
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.StoredLagGraphParams
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasalInitializer
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.DishModel
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedParent
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedEdge
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedFactor
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.Polynomial
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialFunction
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialTerm
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.DefaultTetradLoggerConfig.DefaultEvent
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.DefaultTetradLoggerConfig
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.Beta
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.ChiSquare
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.Discrete
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.Exponential
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.Gamma
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.GaussianPower
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.Indicator
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.LogNormal
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.MixtureOfGaussians
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.Normal
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.Poisson
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.SingleValue
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.Split
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.TruncatedNormal
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.dist.Uniform
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.Matrix
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.Parameters
serializableInstance.
serializableInstance() - Static method in class edu.cmu.tetrad.util.PartialCorrelationPdf
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.PointXy
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.TetradLogger.EmptyConfig
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.Vector
Generates a simple exemplar of this class to test serialization.
serializableInstance() - Static method in class edu.cmu.tetrad.util.Version
Generates a simple exemplar of this class to test serialization.
serializeCurrentDirectory() - Method in class edu.cmu.tetrad.util.TetradSerializableUtils
Finds all classes inside the stated scope that implement TetradSerializable and serializes them out to the getCurrentDirectory() directory.
serialVersionUID - Static variable in interface edu.cmu.tetrad.algcomparison.graph.RandomGraph
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.algcomparison.independence.IndependenceWrapper
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.algcomparison.score.ScoreWrapper
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.algcomparison.simulation.Simulation
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.algcomparison.statistic.Statistic
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.bayes.ManipulatingBayesUpdater
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.calculator.expression.Expression
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.calculator.expression.ExpressionDescriptor
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.calculator.expression.ExpressionSignature
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.data.Covariances
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.data.DataBox
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.data.DataModel
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.data.DataSet
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.data.KnowledgeTransferable
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.data.Simulator
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.data.Variable
Required serial version UID for serialization.
serialVersionUID - Static variable in interface edu.cmu.tetrad.graph.Graph
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.graph.Node
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.sem.ISemIm
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.sem.SemOptimizer
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.GraphRandomizer
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.Initializer
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.RandomDistribution
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.util.dist.Distribution
Constant serialVersionUID=23L
serialVersionUID - Static variable in interface edu.cmu.tetrad.util.Im
Constant serialVersionUID=23L
SESSION - Enum constant in enum class edu.cmu.tetrad.graph.NodeType
Constant SESSION
set(int, double) - Method in class edu.cmu.tetrad.util.Vector
set.
set(int, int, double) - Method in class edu.cmu.tetrad.bayes.CptMapProbs
Sets the probability of the node taking on the value specified by the given row and column to the given value.
set(int, int, double) - Method in class edu.cmu.tetrad.util.Matrix
set.
set(int, int, Number) - Method in class edu.cmu.tetrad.data.ByteDataBox
Sets the value at the given row and column to the given Number.
set(int, int, Number) - Method in interface edu.cmu.tetrad.data.DataBox
Sets the value at the given row and column to the given Number.
set(int, int, Number) - Method in class edu.cmu.tetrad.data.DoubleDataBox
Sets the value at the given row and column to the given Number.
set(int, int, Number) - Method in class edu.cmu.tetrad.data.FloatDataBox
Sets the value at the given row and column to the given Number.
set(int, int, Number) - Method in class edu.cmu.tetrad.data.IntDataBox
Sets the value at the given row and column to the given Number.
set(int, int, Number) - Method in class edu.cmu.tetrad.data.LongDataBox
Sets the value at the given row and column to the given Number.
set(int, int, Number) - Method in class edu.cmu.tetrad.data.MixedDataBox
Sets the value at the given row and column to the given Number.
set(int, int, Number) - Method in class edu.cmu.tetrad.data.ShortDataBox
Sets the value at the given row and column to the given Number.
set(int, int, Number) - Method in class edu.cmu.tetrad.data.VerticalDoubleDataBox
Sets the value at the given row and column to the given Number.
set(int, int, Number) - Method in class edu.cmu.tetrad.data.VerticalIntDataBox
Sets the value at the given row and column to the given Number.
set(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetMap
Sets the sepset for {x, y} to be z.
set(Node, Node, Set<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
Sets the sepset for {x, y} to be z.
set(Node, LinkedHashSet<Node>) - Method in class edu.cmu.tetrad.search.utils.SepsetMap
Sets the parents of x to the (ordered) set z.
set(Node, LinkedHashSet<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
set.
set(String, Object) - Method in class edu.cmu.tetrad.util.Parameters
Sets the given parameter to the given value.
set(String, Object...) - Method in class edu.cmu.tetrad.util.Parameters
Sets the value(s) of the given parameter to a list of strings.
set(String, String) - Method in class edu.cmu.tetrad.util.Parameters
Sets the given parameter to the given value.
set(String, String...) - Method in class edu.cmu.tetrad.util.Parameters
Sets the value(s) of the given parameter to a list of values.
setAdjacencies(Graph) - Method in class edu.cmu.tetrad.search.SvarFges
Sets the set of preset adjacencies for the algorithm; edges not in this adjacencies graph will not be added.
setAdjacencies(Graph) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Sets the set of preset adjacenies for the algorithm; edges not in this adjacencies graph will not be added.
setAdjacencies(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Sets the preset adjacency information for the graph.
setAdjacencyMethod(FaskOrig.AdjacencyMethod) - Method in class edu.cmu.tetrad.search.FaskOrig
Sets the adjacency method used.
setAlgorithm(ComparisonParameters.Algorithm) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field algorithm.
setAlgorithmType(int) - Method in class edu.cmu.tetrad.search.FastIca
If algorithmType == PARALLEL, the components are extracted simultaneously (the default).
setAllowedColliders(Set<Triple>) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Sets the allowed colliders for this object.
setAllowedColliders(Set<Triple>) - Method in interface edu.cmu.tetrad.search.utils.R0R4Strategy
Sets the allowed colliders for the current strategy.
setAllowedColliders(Set<Triple>) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyScoreBased
 
setAllowedColliders(Set<Triple>) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Sets the allowed colliders for the FciOrientDataExaminationStrategy.
setAllowInternalRandomness(boolean) - Method in class edu.cmu.tetrad.search.Grasp
Sets whether to allow internal randomness in the algorithm.
setAllowRandomnessInsideAlgorithm(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Setter for the field allowRandomnessInsideAlgorithm.
setAllValuesToZero() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Assign zero to all elements in the matrix
setAllValuesToZero() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrix
Assign zero to all elements in the matrix
setAllValuesToZero() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrixF
Assign zero to all elements in the matrix
setAllValuesToZero() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.Matrix
Assign zero to all elements in the matrix
setAllValuesToZero() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.MatrixF
Assign zero to all elements in the matrix
setAlpha(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderAlternative
Setter for the field alpha.
setAlpha(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderNull
Setter for the field alpha.
setAlpha(double) - Method in class edu.cmu.tetrad.regression.LogisticRegression
Sets the alpha level.
setAlpha(double) - Method in interface edu.cmu.tetrad.regression.Regression
Sets the significance level at which coefficients are judged to be significant.
setAlpha(double) - Method in class edu.cmu.tetrad.regression.RegressionCovariance
Sets the significance level at which coefficients are judged to be significant.
setAlpha(double) - Method in class edu.cmu.tetrad.regression.RegressionDataset
Sets the significance level at which coefficients are judged to be significant.
setAlpha(double) - Method in class edu.cmu.tetrad.search.BossLingam
Sets the alpha level for the search.
setAlpha(double) - Method in class edu.cmu.tetrad.search.Fask
Sets the significance level for making independence judgments.
setAlpha(double) - Method in class edu.cmu.tetrad.search.FastIca
Sets the FastICA alpha constant in range [1, 2] used in approximation to neg-entropy when 'fun == "logcosh"'
setAlpha(double) - Method in interface edu.cmu.tetrad.search.IndependenceTest
Sets the significance level.
setAlpha(double) - Method in class edu.cmu.tetrad.search.IndTestIod
 
setAlpha(double) - Method in class edu.cmu.tetrad.search.Lofs
Sets the alpha to use, where applicable.
setAlpha(double) - Method in class edu.cmu.tetrad.search.MimbuildTrek
The alpha to use.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.ChiSquareTest
Sets the significance level to be used for tests.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Sets the significance level at which independence judgments should be made.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Sets the significance level.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Sets the significance level.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Sets the significance level at which independence judgments should be made.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
Sets the alpha significance cutoff value.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Sets the alpha significance cutoff value.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Sets the significance level at which independence judgments should be made.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Sets the significance level.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
Sets the alpha value used for checking independence.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestMulti
Sets the significance level for the independence test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestMvpLrt
Sets the significance level of the independence test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Sets the alpha parameter for the probabilistic test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestRegression
Sets the significance level.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Sets the significance level for the independence test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.Kci
Sets the alpha level for the test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.MsepTest
Sets the alpha level for the independence test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Sets the significance level for the independence test.
setAlpha(double) - Method in interface edu.cmu.tetrad.search.work_in_progress.Hbsms
setAlpha.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
setAlpha.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
setAlpha.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Sets the significance level for the independence test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Sets the significance level for the independence test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Sets the significance level.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
Sets the significance level for the independence test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMnlrLr
Sets the significance level for the independence test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
Sets the significance level for the independence test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Set the alpha level for the significance of the test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
Sets the alpha level for the independence test.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Sets the significance level at which independence judgments should be made.
setAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
Sets the significance level.
setAlpha(double) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field alpha.
setAlpha(double) - Method in class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
Sets the significance level of the independence test.
setAlphaPC(double) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Setter for the field alphaPC.
setAlphaSober(double) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Setter for the field alphaSober.
setAmbiguousTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.Dag
Sets the ambiguous triples for the object.
setAmbiguousTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
setAmbiguousTriples.
setAmbiguousTriples(Set<Triple>) - Method in interface edu.cmu.tetrad.graph.Graph
setAmbiguousTriples.
setAmbiguousTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.LagGraph
setAmbiguousTriples.
setAmbiguousTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.SemGraph
setAmbiguousTriples.
setAmbiguousTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Sets the set of ambiguous triples.
setAmbiguousTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.Underlines
Setter for the field ambiguousTriples.
setAntilogCalculated(boolean) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets whether the antilog of each expression level should be calculated.
setAntilogCalculated(boolean) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setAntilogCalculated.
setApplyR1(boolean) - Method in class edu.cmu.tetrad.search.Ccd
Sets whether the R1 rule should be applied.
setApproximate(boolean) - Method in class edu.cmu.tetrad.search.test.Kci
Sets whether the approximate algorithm should be used.
setAutomaticLogDisplayEnabled(boolean) - Method in class edu.cmu.tetrad.util.TetradLogger
States whether log displays should be automatically displayed or not.
setBasalExpression(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Sets the basalExpression.
setBeamWidth(int) - Method in interface edu.cmu.tetrad.search.work_in_progress.Hbsms
setBeamWidth.
setBeamWidth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
setBeamWidth.
setBeamWidth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
setBeamWidth.
setBeta(double) - Method in class edu.cmu.tetrad.algcomparison.statistic.FBetaAdj
Setter for the field beta.
setBeta(DoubleMatrix2D) - Method in class edu.pitt.csb.mgm.Mgm.MGMParams
Sets beta.
setBetaHigh(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Setter for the field betaHigh.
setBetaLow(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Setter for the field betaLow.
setBlockingType(R0R4StrategyTestBased.BlockingType) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Sets the blocking type for the strategy.
setBollenTest(DeltaTetradTest) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
setBollenTest.
setBooleanInfluenceRate(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Sets the rate at which the output of the Glass function influences the change in expression level of a gene.
setBossUseBes(boolean) - Method in class edu.cmu.tetrad.search.BFci
Sets whether the BES should be used.
setBoundGraph(Graph) - Method in class edu.cmu.tetrad.search.Fges
If non-null, edges not adjacent in this graph will not be added.
setBoundGraph(Graph) - Method in class edu.cmu.tetrad.search.FgesMb
If non-null, edges not adjacent in this graph will not be added.
setBoundsEnforced(boolean) - Method in class edu.cmu.tetrad.bayes.DirichletDataSetProbs
True iff bounds checking is performed on variable values indices.
setBThreshold(double) - Method in class edu.cmu.tetrad.search.IcaLingam
The threshold to use for set small elements to zero in the B Hat matrices.
setBThreshold(double) - Method in class edu.cmu.tetrad.search.IcaLingD
Sets the threshold value for the B matrix.
setC(int) - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
Setter for the field c.
setCacheDepthLimit(int) - Method in class edu.cmu.tetrad.search.utils.AdTree
Sets the maximum depth of the cache.
setCanceled(boolean) - Method in class edu.cmu.tetrad.util.TaskManager
Setter for the field canceled.
setCategories(Node, List<String>) - Method in class edu.cmu.tetrad.bayes.BayesPm
Sets the number of values for the given node to the given number.
setCategory(int, int) - Method in class edu.cmu.tetrad.bayes.Proposition
Sets the given value to true and all other values to false for the given variable.
setCategoryNamesDisplayed(boolean) - Method in class edu.cmu.tetrad.data.DiscreteVariable
Sets whether categories for this variable should be displayed.
setCellProbability(int[], double) - Method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
setCellProbability.
setCellTableType(ChiSquareTest.CellTableType) - Method in class edu.cmu.tetrad.search.test.ChiSquareTest
Sets the type of cell table to use.
setCellTableType(ChiSquareTest.CellTableType) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Sets the cell table type.
setCellTableType(ChiSquareTest.CellTableType) - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Sets the cell table type.
setCenter(int, int) - Method in class edu.cmu.tetrad.data.ContinuousVariable
Sets the (x, y) coordinates of the center of this node.
setCenter(int, int) - Method in class edu.cmu.tetrad.data.DiscreteVariable
Sets the (x, y) coordinates of the center of this node.
setCenter(int, int) - Method in class edu.cmu.tetrad.graph.GraphNode
Sets the (x, y) coordinates of the center of this node.
setCenter(int, int) - Method in interface edu.cmu.tetrad.graph.Node
Sets the (x, y) coordinates of the center of this node.
setCenteringComp(JComponent) - Static method in class edu.cmu.tetrad.util.JOptionUtils
Sets the centering component used throughout.
setCenterX(int) - Method in class edu.cmu.tetrad.data.ContinuousVariable
Sets the x coordinate of the center of this node.
setCenterX(int) - Method in class edu.cmu.tetrad.data.DiscreteVariable
Sets the x coordinate of the center of this node.
setCenterX(int) - Method in class edu.cmu.tetrad.graph.GraphNode
Sets the x coordinate of the center of this node.
setCenterX(int) - Method in interface edu.cmu.tetrad.graph.Node
Sets the x coordinate of the center of this node.
setCenterY(int) - Method in class edu.cmu.tetrad.data.ContinuousVariable
Sets the y coordinate of the center of this node.
setCenterY(int) - Method in class edu.cmu.tetrad.data.DiscreteVariable
Sets the y coordinate of the center of this node.
setCenterY(int) - Method in class edu.cmu.tetrad.graph.GraphNode
Sets the y coordinate of the center of this node.
setCenterY(int) - Method in interface edu.cmu.tetrad.graph.Node
Sets the y coordinate of the center of this node.
setCheckType(ClusterSignificance.CheckType) - Method in class edu.cmu.tetrad.search.Bpc
Sets the cluster significance type.
setCheckType(ClusterSignificance.CheckType) - Method in class edu.cmu.tetrad.search.Fofc
Sets which type of cluster check should be performed.
setCheckType(ClusterSignificance.CheckType) - Method in class edu.cmu.tetrad.search.utils.ClusterSignificance
Sets the type of check to perform.
setChipChipVariability(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets the chip to chip variability.
setChipChipVariability(double) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setChipChipVariability.
setClusterName(int, String) - Method in class edu.cmu.tetrad.data.Clusters
setClusterName.
setCoefficient(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialTerm
Sets the coefficient.
setCoefficient(int, int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Sets the coefficient for the given parent of the given factor.
setCoefficient(String, LaggedFactor, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Sets the intercept for the given factor.
setCoefHigh(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Setter for the field coefHigh.
setCoefLow(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Setter for the field coefLow.
setCoefRange(double, double) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
setCoefRange.
setCoefSymmetric(boolean) - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Setter for the field coefSymmetric.
setColliderDiscovery(PcCommon.ColliderDiscovery) - Method in class edu.cmu.tetrad.search.utils.PcCommon
Sets the type of collider discovery to do.
setColumnSpacing(int) - Method in class edu.cmu.tetrad.util.TextTable
Sets the number of spaces between columns, to some number >= 0.
setCompareToTrue(boolean) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Setter for the field compareToTrue.
setComparisonGraph(Comparison.ComparisonGraph) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Sets the comparison graph.
setComparisonGraph(TimeoutComparison.ComparisonGraph) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
The type of graph the results are compared to.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.BFci
Sets whether the complete (Zhang's) rule set should be used.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.Cfci
Sets whether the complete rule set should be used.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.Fci
Sets whether the Zhang complete rule set should be used; false if only R1-R4 (the rule set of the original FCI) should be used.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.FciMax
Sets whether Zhang's complete rule set is used in the search.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.GFci
Sets whether Zhang's complete rules are used.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.GraspFci
Sets whether Zhang's complete rules set is used.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.LvLite
Sets whether the complete rule set should be used during the search algorithm.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.SpFci
Sets whether Zhang's complete rule set is used.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.SvarFci
Sets whether Zhang's complete rule set is to be used.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.SvarGfci
Sets whether the complete rule set is used.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.utils.DagToPag
Setter for the field completeRuleSetUsed.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Sets the flag indicating if the complete rule set is being used.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.utils.TsDagToPag
Setter for the field completeRuleSetUsed.
setCompleteRuleSetUsed(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Sets whether the complete rule set should be used in the IGFci algorithm.
setConfigForClass(Class<?>) - Method in class edu.cmu.tetrad.util.TetradLogger
If there is a pre-defined configuration for the given model it is set, otherwise an exception is thrown.
setConflictRule(PcCommon.ConflictRule) - Method in class edu.cmu.tetrad.search.Cpc
Sets which conflict rule to use for resolving collider orientation conflicts.
setConflictRule(PcCommon.ConflictRule) - Method in class edu.cmu.tetrad.search.Pc
Sets which conflict-rule to use for resolving collider orientation conflicts.
setConflictRule(PcCommon.ConflictRule) - Method in class edu.cmu.tetrad.search.utils.MaxP
Sets the PC conflict rule to use for orientation.
setConflictRule(PcCommon.ConflictRule) - Method in class edu.cmu.tetrad.search.utils.PcCommon
Sets the conflict rule to use.
setCopyData(boolean) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
Setter for the field copyData.
setCorrectResult(Graph) - Method in class edu.cmu.tetrad.study.performance.ComparisonResult
Setter for the field correctResult.
setCountMap(int, CptMapCounts) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Sets the count map for a specific node index in the Bayesian network.
setCovariance(int, int, double) - Method in interface edu.cmu.tetrad.data.Covariances
Sets the covariance at (i, j) to a particular value.
setCovarianceMatrix(ICovarianceMatrix) - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Sets the covariance matrix to be used in the IGFci algorithm.
setCovMatrix(ICovarianceMatrix) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
Setter for the field covMatrix.
setCovMatrix(ICovarianceMatrix) - Method in class edu.cmu.tetrad.sem.SemIm
Sets the sample covariance matrix for this Sem as a submatrix of the given matrix.
setCpdag(boolean) - Method in class edu.cmu.tetrad.search.Dagma
Sets the value of the cpdag field.
setCpdag(boolean) - Method in class edu.cmu.tetrad.search.PermutationSearch
Sets the flag indicating whether a CPDAG (partially directed acyclic graph) is wanted or not.
setCpdagAlgorithm(Cstar.CpdagAlgorithm) - Method in class edu.cmu.tetrad.search.Cstar
The CSTaR algorithm can use any CPDAG algorithm; here you can set it.
setCutoff(double) - Method in class edu.cmu.tetrad.search.Fask
Sets the significance level at which independence judgments should be made.
setCutoff(double) - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Sets the cutoff for the independence test.
setCutoff(double) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.PagSamplingRfci
Set the cutoff.
setCutoffConstrainSearch(double) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Setter for the field cutoffConstrainSearch.
setCutoffDataSearch(double) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Setter for the field cutoffDataSearch.
setData(DataSet) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Setter for the field data.
setDataFile(String) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field dataFile.
setDataFromFile(boolean) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field dataFromFile.
setDataSet(DataSet) - Method in class edu.cmu.tetrad.sem.SemIm
Calculates the covariance matrix of the given DataSet and sets the sample covariance matrix for this model to a subset of it.
setDataType(ComparisonParameters.DataType) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field dataType.
setDecayRate(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Sets the rate at which expression levels tend to return to equilibrium.
setDefaultBw(DataSet, Node) - Method in interface edu.cmu.tetrad.search.utils.Kernel
Sets bandwidth from data using default method
setDefaultBw(DataSet, Node) - Method in class edu.cmu.tetrad.search.utils.KernelGaussian
Sets bandwidth from data using default method
setDefaultToKnowledgeLayout(boolean) - Method in class edu.cmu.tetrad.data.Knowledge
Setter for the field defaultToKnowledgeLayout.
setDefaultValue(Serializable) - Method in class edu.cmu.tetrad.util.ParamDescription
Setter for the field defaultValue.
setDelimiter(char) - Method in class edu.cmu.tetrad.simulation.HsimAutoC
Setter for the field delimiter.
setDelimiter(char) - Method in class edu.cmu.tetrad.simulation.HsimAutoRun
Setter for the field delimiter.
setDelimiter(char) - Method in class edu.cmu.tetrad.simulation.HsimRepeatAC
Setter for the field delimiter.
setDelimiter(char) - Method in class edu.cmu.tetrad.simulation.HsimRepeatAutoRun
Setter for the field delimiter.
setDelimiter(TextTable.Delimiter) - Method in class edu.cmu.tetrad.util.TextTable
Setter for the field delimiter.
setDelta(double) - Method in class edu.cmu.tetrad.search.Fask
Sets the delta value for the current instance of the FaskOrig class.
setDelta(double) - Method in class edu.cmu.tetrad.search.FaskOrig
Sets the delta to use.
setDepth(int) - Method in class edu.cmu.tetrad.search.BFci
Sets the depth of the search (for the constraint-based step).
setDepth(int) - Method in class edu.cmu.tetrad.search.Cfci
Sets the depth--i.e., the maximum number of variables conditioned on in any test.
setDepth(int) - Method in class edu.cmu.tetrad.search.Cpc
Sets the maximum number of variables conditioned on in any conditional independence test.
setDepth(int) - Method in class edu.cmu.tetrad.search.Fas
Sets the maximum depth for the search.
setDepth(int) - Method in class edu.cmu.tetrad.search.Fasd
Sets the depth of the search.
setDepth(int) - Method in class edu.cmu.tetrad.search.Fask
Sets the depth of the search for the Fast Adjacency Search.
setDepth(int) - Method in class edu.cmu.tetrad.search.FaskOrig
Setter for the field depth.
setDepth(int) - Method in class edu.cmu.tetrad.search.Fci
Sets the depth of search, which is the maximum number of variables conditioned on in any test.
setDepth(int) - Method in class edu.cmu.tetrad.search.FciMax
Sets the maximum nubmer of variables conditioned in any test.
setDepth(int) - Method in class edu.cmu.tetrad.search.GFci
Sets the depth of the search for the possible m-sep search.
setDepth(int) - Method in class edu.cmu.tetrad.search.Grasp
Sets the maximum depth of the depth-first search that GRaSP performs while searching for a weakly increasing tuck sequence that improves the score.
setDepth(int) - Method in class edu.cmu.tetrad.search.GraspFci
Sets the depth for the search algorithm.
setDepth(int) - Method in interface edu.cmu.tetrad.search.IFas
Sets the depth of the search--that is, the maximum number of variables conditioned on in the search.
setDepth(int) - Method in class edu.cmu.tetrad.search.LvLite
Sets the maximum size of the separating set used in the graph search algorithm.
setDepth(int) - Method in class edu.cmu.tetrad.search.Pc
Sets the depth of the search--that is, the maximum number of conditioning nodes for any conditional independence checked.
setDepth(int) - Method in class edu.cmu.tetrad.search.Pcd
Sets the depth of the search--that is, the maximum number of conditioning nodes for any conditional independence checked.
setDepth(int) - Method in class edu.cmu.tetrad.search.PcMb
Sets the maximum number of conditioning variables for any conditional independence test.
setDepth(int) - Method in class edu.cmu.tetrad.search.Rfci
Sets the maximum number of variables conditioned on in any test.
setDepth(int) - Method in class edu.cmu.tetrad.search.SpFci
Sets the maximum number of variables conditioned on.
setDepth(int) - Method in class edu.cmu.tetrad.search.SvarFas
Sets the depth of the search--that is, the maximum number of variables conditioned on in the search.
setDepth(int) - Method in class edu.cmu.tetrad.search.SvarFci
Sets the depth of search.
setDepth(int) - Method in class edu.cmu.tetrad.search.utils.Bes
Sets the depth for the search, which is the maximum number of variables conditioned on.
setDepth(int) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
-1 for unlimited depth, otherwise a number >= 0.
setDepth(int) - Method in class edu.cmu.tetrad.search.utils.MaxP
Setter for the field depth.
setDepth(int) - Method in class edu.cmu.tetrad.search.utils.PcCommon
Sets the maximum number of variables conditioned on in any conditional independence test.
setDepth(int) - Method in class edu.cmu.tetrad.search.utils.PossibleMsepFci
Setter for the field depth.
setDepth(int) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyScoreBased
Sets the depth value of the FciOrientDataExaminationStrategyScoreBased object.
setDepth(int) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Sets the depth for the FciOrientDataExaminationStrategy object.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.Dci
Setter for the field depth.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.FasDci
Setter for the field depth.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.FasFdr
Sets the depth of the search--that is, the maximum number of variables conditioned on in the search.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.FasLofs
Setter for the field depth.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Setter for the field depth.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Sets the depth of the search--that is, the maximum number of conditioning nodes for any conditional independence checked.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.Mmhc
Setter for the field depth.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Sets the maximum number of variables conditioned on in any conditional independence test.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Sets the maximum number of variables conditioned on in any conditional independence test.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.VcFas
Setter for the field depth.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Sets the maximum number of variables conditioned on in any conditional independence test.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Sets the maximum number of variables conditioned on in any conditional independence test.
setDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Sets the maximum number of variables conditioned on in any conditional independence test.
setDepth(int) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.PagSamplingRfci
Set the depth.
setDeterminationP(double) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Sets the threshold for making judgments of determination.
setDeterminationP(double) - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Sets the threshold for making judgments of determination.
setDeterminismThreshold(double) - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Setter for the field determinismThreshold.
setDiscount(double) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
setDiscount.
setDiscreteScore(DiscreteScore) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Sets the discrete scoring function to use.
setDiscretize(boolean) - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianLikelihood
Sets whether to discretize child variables to avoid integration.
setDishBumpStDev(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.DishModel
Setter for the field dishBumpStDev.
setDishDishVariability(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets the standard deviation sd% (in percent) of the distribution N(100.0, sd%), from which errors will be drawn for the dish model.
setDishDishVariability(double) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setDishDishVariability.
setDishModel(DishModel) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Sets the dish model.
setDishNumber(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.DishModel
Sets the number of the getModel dish.
setDisplayLogEnabled(boolean) - Method in class edu.cmu.tetrad.util.TetradLogger
Sets whether the display log should be used or not.
setDistribution(Distribution) - Method in class edu.cmu.tetrad.sem.Parameter
Sets the distribution that initial values should be drawn from for this parameter.
setDmStructure(DMSearch.LatentStructure) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Setter for the field dmStructure.
setDoAdjacencySearch(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.Ion
Sets adjacency search on or off
setDoDdpEdgeRemovalStep(boolean) - Method in class edu.cmu.tetrad.search.LvLite
Sets whether to perform DDP edge removal step.
setDoPathLengthSearch(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.Ion
Sets path length search on or off.
setDoR4(boolean) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Sets whether R4 should be run.
setDottedUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.Dag
Sets the dotted underline triples for the given set of Triples.
setDottedUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
setDottedUnderLineTriples.
setDottedUnderLineTriples(Set<Triple>) - Method in interface edu.cmu.tetrad.graph.Graph
setDottedUnderLineTriples.
setDottedUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.LagGraph
setDottedUnderLineTriples.
setDottedUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.SemGraph
setDottedUnderLineTriples.
setDottedUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Sets the dotted underline triples.
setDottedUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.Underlines
Setter for the field dottedUnderLineTriples.
setDouble(int, int, double) - Method in class edu.cmu.tetrad.data.BoxDataSet
Sets the value at the given (row, column) to the given double value, assuming the variable for the column is continuous.
setDouble(int, int, double) - Method in interface edu.cmu.tetrad.data.DataSet
Sets the value at the given (row, column) to the given double value, assuming the variable for the column is continuous.
setDouble(int, int, double) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Sets the value at the given (row, column) to the given double value, assuming the variable for the column is continuous.
setDoubleValue(int, int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Assigns double value x in matrix element (r, c).
setDoubleValue(int, int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrix
Assigns double value x in matrix element (r, c).
setDoubleValue(int, int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrixF
Assigns double value x in matrix element (r, c).
setDoubleValue(int, int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.Matrix
Assigns double value x in matrix element (r, c).
setDoubleValue(int, int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.MatrixF
Assigns double value x in matrix element (r, c).
setEdge(int, int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.Digraph
Sets a value of edge between nodes i and j
setEdge(int, int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Sets a value of edge between nodes i and j
setEdgeChangeTol(int) - Method in class edu.pitt.csb.mgm.ProximalGradient
Positive edge change tolerance is the number of iterations with 0 edge changes needed to converge.
setEdgeCoef(Node, Node, double) - Method in interface edu.cmu.tetrad.sem.ISemIm
setEdgeCoef.
setEdgeCoef(Node, Node, double) - Method in class edu.cmu.tetrad.sem.SemIm
Sets the coefficient value for the edge between two nodes in the graph.
setEdgeCoefficient(Node, Node, double) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
Sets the coefficient for the a->b edge to the given coefficient, if within range.
setEdgeType(EdgeTypeProbability.EdgeType) - Method in class edu.cmu.tetrad.graph.EdgeTypeProbability
Setter for the field edgeType.
setEffectiveSampleSize(int) - Method in interface edu.cmu.tetrad.search.EffectiveSampleSizeSettable
Sets the sample size if the sample size of the data or covariance matrix is not the sample size that should be used by the class.
setEffectiveSampleSize(int) - Method in class edu.cmu.tetrad.search.MarkovCheck
 
setEffectiveSampleSize(int) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
 
setEffectiveSampleSize(int) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Sets the sample size to use for the independence test, which may be different from the sample size of the data set or covariance matrix.
setEffectiveSampleSize(int) - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Sets the sample size if the sample size of the data or covariance matrix is not the sample size that the test should use.
setEffects(LinkedList<Double>) - Method in class edu.cmu.tetrad.search.Ida.NodeEffects
Sets the effects.
setElapsed(long) - Method in class edu.cmu.tetrad.study.performance.ComparisonResult
Setter for the field elapsed.
setEmpirical(boolean) - Method in class edu.cmu.tetrad.search.FaskOrig
Sets whether the empirical option is selected.
setEndpoint(Graph, Node, Node, Endpoint) - Method in class edu.cmu.tetrad.search.utils.DefaultSetEndpointStrategy
Sets the endpoint of a graph given the two nodes and the desired endpoint.
setEndpoint(Graph, Node, Node, Endpoint) - Method in interface edu.cmu.tetrad.search.utils.SetEndpointStrategy
Sets the endpoint of a graph given the two nodes and the desired endpoint.
setEndpoint(Graph, Node, Node, Endpoint) - Method in class edu.cmu.tetrad.search.utils.SvarSetEndpointStrategy
Sets the endpoint of a graph given the two nodes and the desired endpoint.
setEndpoint(Node, Node, Endpoint) - Method in class edu.cmu.tetrad.graph.Dag
Sets the endpoint of a directed edge between two nodes in a graph.
setEndpoint(Node, Node, Endpoint) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Sets the endpoint type at the 'to' end of the edge from 'from' to 'to' to the given endpoint.
setEndpoint(Node, Node, Endpoint) - Method in interface edu.cmu.tetrad.graph.Graph
Sets the endpoint type at the 'to' end of the edge from 'from' to 'to' to the given endpoint.
setEndpoint(Node, Node, Endpoint) - Method in class edu.cmu.tetrad.graph.LagGraph
Sets the endpoint type at the 'to' end of the edge from 'from' to 'to' to the given endpoint.
setEndpoint(Node, Node, Endpoint) - Method in class edu.cmu.tetrad.graph.SemGraph
Sets the endpoint type at the 'to' end of the edge from 'from' to 'to' to the given endpoint.
setEndpoint(Node, Node, Endpoint) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Sets the endpoint of an edge between two nodes in the graph.
setEndpoint1(Endpoint) - Method in class edu.cmu.tetrad.graph.Edge
Setter for the field endpoint1.
setEndpoint2(Endpoint) - Method in class edu.cmu.tetrad.graph.Edge
Setter for the field endpoint2.
setEndpointStrategy(SetEndpointStrategy) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Sets the endpoint strategy for this object.
SetEndpointStrategy - Interface in edu.cmu.tetrad.search.utils
The SetEndpointStrategy interface provides a strategy for setting the endpoint of an edge in a graph.
setEnsureMarkov(boolean) - Method in class edu.cmu.tetrad.search.LvLite
Sets the value indicating whether the process should ensure Markov property.
setEnsureMarkov(boolean) - Method in class edu.cmu.tetrad.search.utils.EnsureMarkov
Sets whether to ensure Markov property.
setEnsureMarkovHelper(EnsureMarkov) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Sets the EnsureMarkov object used by the R0R4StrategyTestBased.
setEpsilon(double) - Method in class edu.cmu.tetrad.search.Lofs
Sets the epsilon value.
setEpsilon(double) - Method in class edu.cmu.tetrad.search.MimbuildTrek
Sets the parameter convergence threshold.
setErrCovar(Node, double) - Method in class edu.cmu.tetrad.sem.SemIm
Setter for the field errCovar.
setErrCovar(Node, Node, double) - Method in class edu.cmu.tetrad.sem.SemIm
Setter for the field errCovar.
setErrorCovariance(Node, Node, double) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
Sets the covariance for the a<->b edge to the given covariance, if within range.
setErrorDistribution(int, Distribution) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Sets the error distribution for the factor'th factor.
setErrorDistribution(int, Distribution) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Method setIntenalNoiseModel
setErrorDistribution(int, Distribution) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialFunction
Method setIntenalNoiseModel
setErrorsNormal(boolean) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Setter for the field errorsNormal.
setErrorsTemplate(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Sets the error template for the software.
setErrVar(Node, double) - Method in interface edu.cmu.tetrad.sem.ISemIm
setErrVar.
setErrVar(Node, double) - Method in class edu.cmu.tetrad.sem.SemIm
Sets the error variance value for a specific node in the model's structural equation.
setEstimated(boolean) - Method in class edu.cmu.tetrad.sem.SemIm
Setter for the field estimated.
setEstimator(EmBayesProperties.Estimator) - Method in class edu.cmu.tetrad.bayes.EmBayesProperties
Setter for the field estimator.
setEventActive(String, boolean) - Method in class edu.cmu.tetrad.util.DefaultTetradLoggerConfig
Sets whether the event associated with the given id is active or not.
setEventActive(String, boolean) - Method in class edu.cmu.tetrad.util.TetradLogger.EmptyConfig
setEventActive.
setEventActive(String, boolean) - Method in interface edu.cmu.tetrad.util.TetradLoggerConfig
Sets whether the event associated with the given id is active or not.
setEvidence(int, int) - Method in class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
setEvidence.
setEvidence(Evidence) - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
Sets new evidence for the updater.
setEvidence(Evidence) - Method in interface edu.cmu.tetrad.bayes.BayesUpdater
Sets new evidence for the updater.
setEvidence(Evidence) - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
Sets new evidence for the updater.
setEvidence(Evidence) - Method in class edu.cmu.tetrad.bayes.Identifiability
Sets new evidence for the updater.
setEvidence(Evidence) - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
Sets new evidence for the updater.
setEvidence(Evidence) - Method in interface edu.cmu.tetrad.bayes.ManipulatingBayesUpdater
Sets new evidence for the updater.
setEvidence(Evidence) - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
Sets new evidence for the updater.
setEvidence(SemEvidence) - Method in class edu.cmu.tetrad.sem.SemUpdater
Sets new evidence for the updater.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Sets the external graph to be used by the algorithm.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Sets the external graph to be used by the algorithm.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Eb
Sets the external graph to be used by the algorithm.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.FaskPw
Sets the external graph to be used by the algorithm.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R1
Sets the external graph for the algorithm.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R2
Sets the external graph for the algorithm.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R3
Sets the external graph to be used by the algorithm.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Rskew
Sets the external graph for this algorithm.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.RskewE
Sets the external graph for the algorithm.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Skew
Sets the external graph to be used by the algorithm.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.SkewE
Sets the external graph to be used by the algorithm.
setExternalGraph(Algorithm) - Method in class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Tanh
Sets the external graph for the algorithm.
setExternalGraph(Algorithm) - Method in interface edu.cmu.tetrad.algcomparison.utils.TakesExternalGraph
setExternalGraph.
setExternalGraph(Graph) - Method in class edu.cmu.tetrad.search.Fasd
Sets the external graph.
setExternalGraph(Graph) - Method in class edu.cmu.tetrad.search.Fask
Sets the initial graph for the FaskOrig class.
setExternalGraph(Graph) - Method in class edu.cmu.tetrad.search.FaskOrig
Sets the external graph to use.
setExternalGraph(Graph) - Method in class edu.cmu.tetrad.search.SvarFas
Sets an external graph.
setExternalGraph(Graph) - Method in class edu.cmu.tetrad.search.SvarFges
Sets the initial graph.
setExternalGraph(Graph) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Sets the initial graph.
setExternalGraph(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.VcFas
Setter for the field externalGraph.
setExtraEdgeRemovalStyle(LvLite.ExtraEdgeRemovalStyle) - Method in class edu.cmu.tetrad.search.LvLite
Sets the style for removing extra edges.
setExtraEdgeThreshold(double) - Method in class edu.cmu.tetrad.search.Fask
` Sets the extra-edge threshold for the FaskOrig class.
setFactor(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Sets the factor.
setFactor(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedFactor
Sets the name of the lagged factor
setFacts() - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
setFacts.
setFacts(IndependenceFacts) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Setter for the field facts.
setFacts(IndependenceFacts) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Setter for the field facts.
setFaithfulnessAssumed(boolean) - Method in class edu.cmu.tetrad.search.Fges
Sets whether one-edge faithfulness should be assumed.
setFaithfulnessAssumed(boolean) - Method in class edu.cmu.tetrad.search.FgesMb
Sets whether one-edge faithfulness should be assumed.
setFaithfulnessAssumed(boolean) - Method in class edu.cmu.tetrad.search.GFci
Sets whether one-edge faithfulness is assumed.
setFaithfulnessAssumed(boolean) - Method in class edu.cmu.tetrad.search.SvarFges
Set to true if it is assumed that all path pairs with one length 1 path do not cancel.
setFaithfulnessAssumed(boolean) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Set to true if it is assumed that all path pairs with one length 1 path do not cancelAll.
setFaithfulnessAssumed(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Sets whether faithfulness is assumed in the IGFci algorithm.
setFaithfulnessAssumed(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Sets the faithfulness assumption status for the current instance.
setFasType(PcCommon.FasType) - Method in class edu.cmu.tetrad.search.utils.PcCommon
Setter for the field fasType.
setFdr(boolean) - Method in class edu.cmu.tetrad.search.Pcd
Sets whether this test will run with False Discovery Rate tests.
setFdr(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Sets the value of the fdr field.
setFileLoggingEnabled(boolean) - Method in class edu.cmu.tetrad.util.TetradLogger
Sets whether "file logging" is enabled or not; that is whether calls to setNextOutputStream will be respected.
setFilename(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.StoredLagGraphParams
Sets the stored file.
setFilenameOut(String) - Method in class edu.cmu.tetrad.simulation.HsimAutoC
Setter for the field filenameOut.
setFilenameOut(String) - Method in class edu.cmu.tetrad.simulation.HsimAutoRun
Setter for the field filenameOut.
setFilenameOut(String) - Method in class edu.cmu.tetrad.simulation.HsimRepeatAC
Setter for the field filenameOut.
setFilenameOut(String) - Method in class edu.cmu.tetrad.simulation.HsimRepeatAutoRun
Setter for the field filenameOut.
setFindMb(boolean) - Method in class edu.cmu.tetrad.search.PcMb
Setter for the field findMb.
setFindSmallestSubset(boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
Sets the flag indicating whether a smallest subset of each conditioning set yielding independence should be reported.
setFirstStepStored(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets the index of the first step to actually be stored out.
setFirstStepStored(int) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setFirstStepStored.
setFixed(boolean) - Method in class edu.cmu.tetrad.sem.Parameter
Sets whether this parameter should be held fixed during estimation.
setFixedParamValue(Parameter, double) - Method in interface edu.cmu.tetrad.sem.ISemIm
setFixedParamValue.
setFixedParamValue(Parameter, double) - Method in class edu.cmu.tetrad.sem.SemIm
Sets the fixed value for a specified parameter in the model.
setFlatPrior(boolean) - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbsParams
Setter for the field flatPrior.
setForbidden(String, String) - Method in class edu.cmu.tetrad.data.Knowledge
Marks the edge var1 --> var2 as forbid.
setForwardSearch(boolean) - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
Setter for the field forwardSearch.
setFreeParamValues(double[]) - Method in interface edu.cmu.tetrad.sem.ISemIm
setFreeParamValues.
setFreeParamValues(double[]) - Method in class edu.cmu.tetrad.sem.SemIm
Sets the values of the free freeParameters (in the order in which they appear in getFreeParameters()) to the values contained in the given array.
setFunction(int) - Method in class edu.cmu.tetrad.search.FastIca
Sets the function type to be used, either LOGCOSH or EXP.
setGamma(double) - Method in class edu.cmu.tetrad.search.score.EbicScore
Sets the gamma parameter for EBIC.
setGammaHigh(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Setter for the field gammaHigh.
setGammaLow(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Setter for the field gammaLow.
setGesDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Setter for the field gesDepth.
setGraph(Dag) - Method in class edu.cmu.tetrad.graph.LagGraph
Setter for the field graph.
setGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.independence.MSeparationTest
Setter for the field graph.
setGraph(Graph) - Method in interface edu.cmu.tetrad.algcomparison.independence.TakesGraph
setGraph.
setGraph(Graph) - Method in class edu.cmu.tetrad.algcomparison.score.MSeparationScore
Setter for the field graph.
setGraph(Graph) - Method in class edu.cmu.tetrad.bayes.EmBayesProperties
Setter for the field graph.
setGraph(Graph) - Method in class edu.cmu.tetrad.search.utils.DagSepsets
 
setGraph(Graph) - Method in interface edu.cmu.tetrad.search.utils.SepsetProducer
Sets the graph for the SepsetProducer object.
setGraph(Graph) - Method in class edu.cmu.tetrad.search.utils.SepsetsGreedy
Sets the graph for the Sepsets object.
setGraph(Graph) - Method in class edu.cmu.tetrad.search.utils.SepsetsMaxP
Sets the graph for the SepsetsMaxP object.
setGraph(Graph) - Method in class edu.cmu.tetrad.search.utils.SepsetsMinP
Sets the graph for the Sepsets object.
setGraph(Graph) - Method in class edu.cmu.tetrad.search.utils.SepsetsPossibleMsep
 
setGraph(Graph) - Method in class edu.cmu.tetrad.search.utils.SepsetsSet
 
setGraph(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Setter for the field graph.
setGraph(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Setter for the field graph.
setGraph(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Setter for the field graph.
setGraph(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Setter for the field graph.
setGraph(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Setter for the field graph.
setGraphFile(String) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field graphFile.
setGraphName(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Sets the name of the graph
setGraphNum(int) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field graphNum.
setGuaranteeCpdag(boolean) - Method in class edu.cmu.tetrad.search.Cpc
Sets to true just in case the algorithm should guarantee that the output is consistent with a CPDAG, i.e., no bidirected edges and no actual or implied cycles.
setGuaranteeCpdag(boolean) - Method in class edu.cmu.tetrad.search.Pc
Sets whether cycles should be checked.
setGuaranteeCpdag(boolean) - Method in class edu.cmu.tetrad.search.Pcd
Sets whether the algorithm should prevent cycles during the search.
setGuaranteeCpdag(boolean) - Method in class edu.cmu.tetrad.search.utils.PcCommon
Sets to true just in case edges will not be added if they create cycles.
setGuaranteeCpdag(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Sets the flag to determine whether to guarantee a CPDAG (Consensus Partially Directed Acyclic Graph) result in the search.
setGuaranteeIid(boolean) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Setter for the field guaranteeIid.
setGuaranteePag(boolean) - Method in class edu.cmu.tetrad.search.BFci
Sets whether to guarantee the output is a PAG by repairing a faulty PAG.
setGuaranteePag(boolean) - Method in class edu.cmu.tetrad.search.Fci
Sets whether to guarantee the output is a PAG by repairing a faulty PAG.
setGuaranteePag(boolean) - Method in class edu.cmu.tetrad.search.FciMax
Sets whether to guarantee a PAG.
setGuaranteePag(boolean) - Method in class edu.cmu.tetrad.search.GFci
Sets the flag indicating whether to guarantee the output is a legal PAG.
setGuaranteePag(boolean) - Method in class edu.cmu.tetrad.search.GraspFci
Sets the flag for whether to guarantee the output is a legal PAG.
setGuaranteePag(boolean) - Method in class edu.cmu.tetrad.search.LvLite
Sets whether to guarantee a PAG output by repairing a faulty PAG.
setGuaranteePag(boolean) - Method in class edu.cmu.tetrad.search.SpFci
Sets whether the search should guarantee the output is a legal PAG.
setGuaranteePag(boolean) - Method in class edu.cmu.tetrad.search.SvarFci
Sets whether a guaranteed partial ancestral graph (PAG) should be built during the search.
setHighlighted(boolean) - Method in class edu.cmu.tetrad.graph.Edge
Setter for the field highlighted.
setHighPValueAlpha(double) - Method in interface edu.cmu.tetrad.search.work_in_progress.Hbsms
setHighPValueAlpha.
setHighPValueAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
setHighPValueAlpha.
setHighPValueAlpha(double) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
setHighPValueAlpha.
setHistory(GeneHistory) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets the history.
setHistory(GeneHistory) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setHistory.
setIa(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Setter for the field ia.
setIncludeDishAndChipColumns(boolean) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
setIncludeDishAndChipColumns.
setIncludeDishAndChipVariables(boolean) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
Setter for the field includeDishAndChipVariables.
setIncludeNegativeCoefs(boolean) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Setter for the field includeNegativeCoefs.
setIncludePositiveCoefs(boolean) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Setter for the field includePositiveCoefs.
setIncompleteCholesky(double) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Sets the precision for the Incomplete Choleksy factorization method for approximating Gram matrices.
setIndegree(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Setter for the field indegree.
setIndegreeType(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Setter for the field indegreeType.
setIndependenceTest(IndependenceTest) - Method in class edu.cmu.tetrad.search.MarkovCheck
Sets the independence test to be used for determining independence between variables.
setIndependenceTest(IndependenceTest) - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Sets the independence test for the IGFci algorithm.
setIndependenceTest(ComparisonParameters.IndependenceTestType) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field independenceTest.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Sets the independence wrapper for the object.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Sets the independence wrapper.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Sets the independence wrapper.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Sets the independence wrapper.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cpc
Sets the independence wrapper for the algorithm.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Sets the independence wrapper.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fas
Sets the independence wrapper.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Sets the independence wrapper.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pc
Sets the independence wrapper.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMb
Sets the independence wrapper.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Sets the IndependenceWrapper object for this algorithm.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Ccd
Updates the independence wrapper for this algorithm.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci
Sets the independence wrapper for the algorithm.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci
Sets the IndependenceWrapper object associated with this method.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax
Sets the independence wrapper for the algorithm.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Sets the independence wrapper for the algorithm.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Sets the independence wrapper.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
 
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci
Sets the independence wrapper.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Sets the IndependenceWrapper object for the algorithm.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarFci
Sets the independence wrapper for the algorithm.
setIndependenceWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Sets the independence wrapper for the algorithm.
setIndependenceWrapper(IndependenceWrapper) - Method in interface edu.cmu.tetrad.algcomparison.utils.TakesIndependenceWrapper
Sets the independence wrapper.
setIndices(int[]) - Method in class edu.cmu.tetrad.util.IndexedMatrix
Sets the index array.
setIndTestWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Sets a test wrapper if not null.
setIndTestWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskLofsConcatenated
Sets a test wrapper if not null.
setIndTestWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Sets a test wrapper if not null.
setIndTestWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Sets a test wrapper if not null.
setIndTestWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Sets a test wrapper if not null.
setIndTestWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Sets the IndependenceWrapper for this algorithm.
setIndTestWrapper(IndependenceWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Sets a test wrapper if not null.
setIndTestWrapper(IndependenceWrapper) - Method in interface edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm
Sets a test wrapper if not null.
setInhibitExcite(int[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Sets the inhibit/excite.
setInitialAllowedColliders(HashSet<Triple>) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Sets the initial allowed colliders for the strategy.
setInitialAllowedColliders(HashSet<Triple>) - Method in interface edu.cmu.tetrad.search.utils.R0R4Strategy
Sets the initial allowed colliders for the current strategy.
setInitialAllowedColliders(HashSet<Triple>) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Sets the initial set of allowed colliders for the FciOrientDataExaminationStrategy.
setInitialGraph(Graph) - Method in class edu.cmu.tetrad.search.Fges
Sets the initial graph for the application.
setInitialGraph(Graph) - Method in class edu.cmu.tetrad.search.FgesMb
Sets the initial graph for the software.
setInitialGraph(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Sets the initial graph, ensuring the graph's nodes match the expected variables.
setInitializedRandomly(boolean) - Method in class edu.cmu.tetrad.sem.Parameter
Set to true iff this parameter should be initialized randomly by drawing an initial value from its preset random distribution.
setInitSync(boolean) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Sets whether initialization should be synchronized.
setInitSync(boolean) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets whether the expression levels of cells should be synchronized on initialization.
setInitSync(boolean) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setInitSync.
setInputs(int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Setter for the field inputs.
setInt(int, int, int) - Method in class edu.cmu.tetrad.data.BoxDataSet
Sets the value at the given (row, column) to the given int value, assuming the variable for the column is discrete.
setInt(int, int, int) - Method in interface edu.cmu.tetrad.data.DataSet
Sets the value at the given (row, column) to the given int value, assuming the variable for the column is discrete.
setInt(int, int, int) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Sets the value at the given (row, column) to the given int value, assuming the variable for the column is discrete.
setIntercept(int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Sets the intercept for the given factor.
setIntercept(Node, double) - Method in interface edu.cmu.tetrad.sem.ISemIm
setIntercept.
setIntercept(Node, double) - Method in class edu.cmu.tetrad.sem.SemIm
Sets the intercept for a specified node in the SEM model.
setIntercept(String, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Sets the intercept for the given factor.
setInterceptHigh(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Setter for the field interceptHigh.
setInterceptLow(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Setter for the field interceptLow.
setInterval(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Returns the interval (int time steps) between time steps stored out.
setInterval(int) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setInterval.
setIpen(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Setter for the field ipen.
setIs(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Setter for the field is.
setItr(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Setter for the field itr.
setJustification(int) - Method in class edu.cmu.tetrad.util.TextTable
Sets the justification, either LEFT_JUSTIFIED or RIGHT_JUSTIFIED.
setKAddition(double) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Sets the value of k_addition.
setKDeletion(double) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Sets the value of k_deletion.
setKernelType(Kci.KernelType) - Method in class edu.cmu.tetrad.search.test.Kci
Sets the type of kernel to be used in computations.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Fofc
Sets the knowledge associated with this object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.cluster.Ftfc
Sets the knowledge associated with this algorithm.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Sets the knowledge associated with this object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Sets the knowledge associated with this object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskLofsConcatenated
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FasLofs
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Sets the knowledge object for this instance.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Boss
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossLingam
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cpc
Sets the knowledge associated with this object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fas
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMb
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMeasurement
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pc
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pcd
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMb
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.SingleGraphAlg
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Sp
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Sets the knowledge associated with the algorithm.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossDumb
Sets the knowledge object associated with this method.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPag
Sets the knowledge object associated with this method.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci
Sets the knowledge object for the algorithm.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci
Sets the knowledge object for this method.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax
Sets the knowledge associated with the algorithm.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Sets the Knowledge object associated with this instance.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Sets the knowledge object associated with this method.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
Sets the knowledge object associated with this method.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci
Sets the knowledge associated with this method.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.RfciBsc
Sets the knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Sets the knowledge object associated with this algorithm.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarFci
Sets the knowledge object associated with this algorithm.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Sets the knowledge associated with this object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Sets the knowledge for the current instance.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.algcomparison.statistic.KnowledgeSatisfied
 
setKnowledge(Knowledge) - Method in interface edu.cmu.tetrad.algcomparison.utils.HasKnowledge
Sets a knowledge object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.data.BoxDataSet
Sets knowledge to a copy of the given object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Sets the knowledge associated with the ICovarianceMatrix.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Sets the knowledge associated with the ICovarianceMatrix.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Sets the knowledge associated with the ICovarianceMatrix.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.data.DataModelList
Sets knowledge to a copy of the given object.
setKnowledge(Knowledge) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Sets the knowledge associated with the ICovarianceMatrix.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.data.IndependenceFacts
Sets knowledge to a copy of the given object.
setKnowledge(Knowledge) - Method in interface edu.cmu.tetrad.data.KnowledgeTransferable
Sets knowledge to a copy of the given object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Sets knowledge to a copy of the given object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.data.TimeSeriesData
Sets knowledge to a copy of the given object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.BFci
Sets the knowledge to be used for the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Boss
Sets the knowledge to be used for the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Cfci
Set the knowledge used in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Cpc
Sets the knowledge specification used in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Fas
Sets the knowledge for this object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Fasd
Sets the knowledge for this object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Fask
Sets the knowledge object for the current instance.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.FaskOrig
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Fci
Sets background knowledge for the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.FciMax
Sets background knowledge for the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Fges
Sets the background knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.FgesMb
Sets the background knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.GFci
Sets the knowledge to use in search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Grasp
Sets the knowledge used in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.GraspFci
Sets the knowledge used in search.
setKnowledge(Knowledge) - Method in interface edu.cmu.tetrad.search.IFas
Sets the knowledge for the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Lofs
Sets the knowledge for the object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.LvDumb
Sets the knowledge used in search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.LvLite
Sets the knowledge used in search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.MarkovCheck
Sets the knowledge object for the Markov checker.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Mimbuild
Sets the knowledge to be used in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.MimbuildTrek
The knowledge to use in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Pc
Sets the knowledge specification to be used in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Pcd
Sets the knowledge object used by this method.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.PcMb
Sets knowledge, to which the algorithm is in fact sensitive.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.PermutationSearch
Sets the knowledge to be used for the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Rfci
Sets the knowledge used in search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.Sp
Sets the knowledge associated with this object.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.SpFci
Sets the knoweldge used in the search.
setKnowledge(Knowledge) - Method in interface edu.cmu.tetrad.search.SuborderSearch
The knowledge being used.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.SvarFas
Sets the knowledge for the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.SvarFci
Sets the knowledge for the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.SvarFges
Sets the background knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.SvarGfci
Sets the knowledge for the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.Bes
Sets the knowledge for the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.BesPermutation
Sets the knowledge that BES will use.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.DagToPag
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Sets the knowledge to use for the final orientation.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Sets the background knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.MaxP
Sets the knowledge to use for orientation.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.MeekRules
Sets the knowledge to be used in the orientation.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.PcCommon
Sets the knowledge specification used in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.PossibleMsepFci
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in interface edu.cmu.tetrad.search.utils.R0R4Strategy
Sets the knowledge object to be used by the strategy.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyScoreBased
Sets the Knowledge object for this instance.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Sets the knowledge object used by the FciOrientDataExaminationStrategy.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.utils.TsDagToPag
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.FasDci
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.FasFdr
Sets the knowledge for the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.FaskVote
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.FasLofs
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in interface edu.cmu.tetrad.search.work_in_progress.Hbsms
setKnowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam
setKnowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsGes
setKnowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Sets the knowledge for the IGFci algorithm.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.Ion
Sets the knowledge to be used for this search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Sets the background knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Sets the knowledge specification to be used in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.Mmhc
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Sets the knowledge specification used in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Sets the knowledge specification used in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.VcFas
Setter for the field knowledge.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Sets the knowledge specification used in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Sets the knowledge specification used in the search.
setKnowledge(Knowledge) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Sets the knowledge specification used in the search.
setKnowledge(Knowledge) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.PagSamplingRfci
Set the knowledge.
setKnowledge(List<Node>, List<Node>) - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
setKnowledge.
setKnowledgeGroup(int, KnowledgeGroup) - Method in class edu.cmu.tetrad.data.Knowledge
Legacy, do not use.
setKReorientation(double) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Sets the value of the K-reorientation parameter.
setLambda(double) - Method in class edu.cmu.tetrad.search.score.GicScores
Sets the lambda parameter.
setLambda(double) - Method in class edu.cmu.tetrad.search.score.PoissonPriorScore
Sets the lambda parameter.
setLambda1(double) - Method in class edu.cmu.tetrad.search.Dagma
Sets the value of lambda1.
setLeftRight(Fask.LeftRight) - Method in class edu.cmu.tetrad.search.Fask
Sets the left-right rule used.
setLeftRight(FaskOrig.LeftRight) - Method in class edu.cmu.tetrad.search.FaskOrig
Sets the left-right rule used
setLevel(OutputStream, Level) - Method in class edu.cmu.tetrad.util.LogUtils
Sets the logging level for the given stream.
setLinearHigh(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Setter for the field linearHigh.
setLinearLow(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Setter for the field linearLow.
setLocation(String, PointXy) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Sets the location.
setLocation(String, PointXy) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Sets the location.
setLocation(String, PointXy) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Sets the location.
setLocation(String, PointXy) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Sets the location.
setLocationMap(DataSet) - Method in class edu.cmu.tetrad.simulation.GdistanceRandom
Setter for the field locationMap.
setLog(boolean) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Sets whether log output should be produced.
setLogging(boolean) - Method in class edu.cmu.tetrad.util.TetradLogger
Sets whether the logger is on or not.
setLoggingDirectory(String) - Method in class edu.cmu.tetrad.util.TetradLogger
Sets the logging directory, but first checks whether we can write to it, etc.
setLoggingFilePrefix(String) - Method in class edu.cmu.tetrad.util.TetradLogger
Sets the logging prefix.
setLongDescription(String) - Method in class edu.cmu.tetrad.util.ParamDescription
Setter for the field longDescription.
setLowerBound(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction
Sets the lower bound for expression levels.
setLowerBound(double) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Sets the lower bound.
setLowerBoundDouble(double) - Method in class edu.cmu.tetrad.util.ParamDescription
Setter for the field lowerBoundDouble.
setLowerBoundInt(int) - Method in class edu.cmu.tetrad.util.ParamDescription
Setter for the field lowerBoundInt.
setLowerBoundLong(long) - Method in class edu.cmu.tetrad.util.ParamDescription
Setter for the field lowerBoundLong.
setMag(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Sets the MAG to wrap.
setMag(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Sets the MAG to wrap.
setMag(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Sets the MAG to wrap.
setManipulated(int, boolean) - Method in class edu.cmu.tetrad.bayes.Evidence
setManipulated.
setManipulated(int, boolean) - Method in class edu.cmu.tetrad.bayes.Manipulation
Setter for the field manipulated.
setManipulated(int, boolean) - Method in class edu.cmu.tetrad.sem.SemEvidence
setManipulated.
setManipulated(int, boolean) - Method in class edu.cmu.tetrad.sem.SemManipulation
Setter for the field manipulated.
setMatrix(Matrix) - Method in class edu.cmu.tetrad.data.CorrelationMatrix
Sets the covariance matrix.
setMatrix(Matrix) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Sets the covariance matrix.
setMatrix(Matrix) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Sets the covariance matrix.
setMatrix(Matrix) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Sets the covariance matrix.
setMatrix(Matrix) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Sets the covariance matrix.
setMaxBlockingPathLength(int) - Method in class edu.cmu.tetrad.search.LvLite
Sets the maximum length of any discriminating path.
setMaxCacheSize(int) - Method in class edu.cmu.tetrad.search.utils.AdTree
Sets the maximum size of the cache.
setMaxDdpPathLength(int) - Method in class edu.cmu.tetrad.search.LvLite
Sets the maximum DDP path length.
setMaxDegree(int) - Method in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Sets the maximum degree of any nodes in the graph.
setMaxDegree(int) - Method in class edu.cmu.tetrad.search.Fges
The maximum of parents any nodes can have in the output pattern.
setMaxDegree(int) - Method in class edu.cmu.tetrad.search.FgesMb
The maximum of parents any nodes can have in the output pattern.
setMaxDegree(int) - Method in class edu.cmu.tetrad.search.GFci
Sets the maximum indegree of the output graph.
setMaxDegree(int) - Method in class edu.cmu.tetrad.search.SpFci
Sets the max degree of the search.
setMaxDegree(int) - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Sets the maximum degree for the graph.
setMaxDegree(int) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
The maximum of parents any nodes can have in an output pattern.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.BFci
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.Cfci
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.Fci
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.FciMax
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.GFci
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.GraspFci
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.Rfci
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.SpFci
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.SvarFci
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.SvarGfci
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.utils.MaxP
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.utils.PcCommon
Setter for the field maxPathLength.
setMaxDiscriminatingPathLength(int) - Method in class edu.cmu.tetrad.search.utils.TsDagToPag
Sets the maximum length of any discriminating path.
setMaxDiscriminatingPathLength(int) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.PagSamplingRfci
Sets the maximum length of any discriminating path.
setMaxEdges(int) - Method in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Sets the maximum number of edges in the graph.
setMaxIndegree(int) - Method in class edu.cmu.tetrad.search.SvarFges
The maximum of parents any nodes can have in the output pattern.
setMaxInDegree(int) - Method in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Sets the maximum indegree of any node in the graph.
setMaxit(int) - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Setter for the field maxit.
setMaxIterations(int) - Method in class edu.cmu.tetrad.cluster.KMeans
Sets the maximum number of iterations, or -1 if the algorithm is allowed to run unconstrainted.
setMaxIterations(int) - Method in class edu.cmu.tetrad.search.FastIca
Sets the maximum number of iterations to allow.
setMaxLag(int) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Setter for the field maxLag.
setMaxLagAllowable(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph
Sets the maximum allowable lag.
setMaxLagAllowable(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
Sets the maximum allowable lag.
setMaxLagAllowable(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Sets the maximum allowable lag.
setMaxLagAllowable(int) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Sets the maximum allowable lag.
setMaxLength(int) - Method in class edu.cmu.tetrad.search.MarkovCheck
Sets the maximum path length for relevant paths.
setMaxLength(int) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Sets the maximum length for relevant paths.
setMaxNumShifts(int) - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
Setter for the field maxNumShifts.
setMaxOutDegree(int) - Method in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Sets the maximum outdegree of any node in the graph.
setMaxPathLength(int) - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Sets the maximum length for any path in the graph.
setMaxReachablePathLength(int) - Method in class edu.cmu.tetrad.search.Cfci
Sets the maximum length for any discriminating path.
setMaxReachablePathLength(int) - Method in class edu.cmu.tetrad.search.utils.PossibleMsepFci
Sets the maximum reachable path length for the search algorithm.
setMaxShift(int) - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
Setter for the field maxShift.
setMean(Node, double) - Method in interface edu.cmu.tetrad.sem.ISemIm
setMean.
setMean(Node, double) - Method in class edu.cmu.tetrad.sem.SemIm
Sets the mean value for a given node in the variableNodes list.
setMeanHigh(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Setter for the field meanHigh.
setMeanLow(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Setter for the field meanLow.
setMeanRange(double, double) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
setMeanRange.
setMeanStandardDeviation(Node, double) - Method in class edu.cmu.tetrad.sem.SemIm
Sets the mean associated with the given node.
setMeasuredDataSaved(boolean) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets whether measured data should be saved out for this simulation.
setMedianBandwidth(DataSet, Node) - Method in class edu.cmu.tetrad.search.utils.KernelGaussian
Sets the bandwidth of the kernel to median distance between two points in the given vector
setMeekPreventCycles(boolean) - Method in class edu.cmu.tetrad.search.PcMb
Sets whether cycles should be prevented, using a cycle checker.
setMeekPreventCycles(boolean) - Method in class edu.cmu.tetrad.search.utils.MeekRules
Sets whether cycles should be prevented by cycle checking.
setMeekPreventCycles(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Sets to true just in case edges will not be added if they would create cycles.
setMeekPreventCycles(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Sets to true just in case the output is guaranteed to be compatible with a CPDAG--i.e., no bidirected edges and no actual or implied cycles due to the Meek rules.
setMeekPreventCycles(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Sets to true just in case edges will not be added if they would create cycles.
setMeekPreventCycles(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Sets to true just in case edges will not be added if they would create cycles.
setMeekPreventCycles(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Sets to true just in case edges will not be added if they would create cycles.
setMethod(int) - Method in class edu.cmu.tetrad.data.ContinuousDiscretizationSpec
Sets the method used for discretization.
setMinClusterSize(int) - Method in class edu.cmu.tetrad.search.Mimbuild
Setter for the field minClusterSize.
setMinClusterSize(int) - Method in class edu.cmu.tetrad.search.MimbuildTrek
Sets the minimum cluster size.
setMinCountPerCell(double) - Method in class edu.cmu.tetrad.search.test.ChiSquareTest
The minimum number of counts per conditional table for chi-square for that table and its degrees of freedom to be included in the overall chi-square and degrees of freedom.
setMinCountPerCell(double) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
The minimum number of counts per conditional table for chi-square for that table and its degrees of freedom to be included in the overall chi-square and degrees of freedom.
setMinCountPerCell(double) - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
The minimum number of counts per conditional table for chi-square for that table and its degrees of freedom to be included in the overall chi-square and degrees of freedom.
setMinDiscount(int) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Setter for the field minDiscount.
setMinSampleSizePerCell(int) - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianLikelihood
Sets the minimum sample size per cell.
setMinSampleSizePerCell(int) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Sets the minimum sample size per cell for the independence test.
setMlag(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Setter for the field mlag.
setMlag(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraphParams
Sets the maximum lag.
setN(int) - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Setter for the field n.
setName(String) - Method in class edu.cmu.tetrad.data.AbstractVariable
Sets the name of this node.
setName(String) - Method in class edu.cmu.tetrad.data.BoxDataSet
Sets the name of the data model (may be null).
setName(String) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Sets the name of the covariance matrix.
setName(String) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Sets the name of the covariance matrix.
setName(String) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Sets the name of the covariance matrix.
setName(String) - Method in interface edu.cmu.tetrad.data.DataModel
Sets the name of the data model (may be null).
setName(String) - Method in class edu.cmu.tetrad.data.DataModelList
Sets the name of the data model (may be null).
setName(String) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Sets the name of the covariance matrix.
setName(String) - Method in class edu.cmu.tetrad.data.IndependenceFacts
Sets the name of the data model (may be null).
setName(String) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Sets the name of the data model (may be null).
setName(String) - Method in class edu.cmu.tetrad.data.TimeSeriesData
Sets the name of the data model (may be null).
setName(String) - Method in class edu.cmu.tetrad.graph.GraphNode
Sets the name of this node.
setName(String) - Method in interface edu.cmu.tetrad.graph.Node
Sets the name of this node.
setName(String) - Method in class edu.cmu.tetrad.sem.Parameter
Sets the name for this parameter.
setName(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Sets the name.
setName(String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Sets the name of this matrix
setNaturalEdgeLength(double) - Method in class edu.cmu.tetrad.graph.LayoutUtil.KamadaKawaiLayout
Sets the natural length of an edge.
setNextOutputStream() - Method in class edu.cmu.tetrad.util.TetradLogger
Sets the next output stream to use it for logging, call removeNextOutputStream to remove it.
setNoData(boolean) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field noData.
setNodeExpression(Node, String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Sets the expression for a given node.
setNodeName(int, String) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Sets the name of node i in this graph
setNodes(List<Node>) - Method in class edu.cmu.tetrad.data.IndependenceFacts
Setter for the field nodes.
setNodes(List<Node>) - Method in class edu.cmu.tetrad.graph.Dag
Set the nodes of the graph.
setNodes(List<Node>) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
setNodes.
setNodes(List<Node>) - Method in interface edu.cmu.tetrad.graph.Graph
setNodes.
setNodes(List<Node>) - Method in class edu.cmu.tetrad.graph.LagGraph
setNodes.
setNodes(List<Node>) - Method in class edu.cmu.tetrad.graph.SemGraph
setNodes.
setNodes(List<Node>) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Sets the nodes of the graph.
setNodes(List<Node>) - Method in class edu.cmu.tetrad.search.Ida.NodeEffects
Sets the nodes.
setNodeType(NodeType) - Method in class edu.cmu.tetrad.data.ContinuousVariable
Sets the node type for this node.
setNodeType(NodeType) - Method in class edu.cmu.tetrad.data.DiscreteVariable
Sets the node type for this node.
setNodeType(NodeType) - Method in class edu.cmu.tetrad.graph.GraphNode
Sets the node type for this node.
setNodeType(NodeType) - Method in interface edu.cmu.tetrad.graph.Node
Sets the node type for this node.
setNodeVariableType(NodeVariableType) - Method in class edu.cmu.tetrad.data.ContinuousVariable
Sets the type (domain, interventional status, interventional value..) for this node variable
setNodeVariableType(NodeVariableType) - Method in class edu.cmu.tetrad.data.DiscreteVariable
Sets the type (domain, interventional status, interventional value..) for this node variable
setNodeVariableType(NodeVariableType) - Method in class edu.cmu.tetrad.graph.GraphNode
Sets the type (domain, interventional status, interventional value..) for this node variable
setNodeVariableType(NodeVariableType) - Method in interface edu.cmu.tetrad.graph.Node
Sets the type (domain, interventional status, interventional value..) for this node variable
setNonSingularDepth(int) - Method in class edu.cmu.tetrad.search.Grasp
Sets the maximum depth at which singular tucks can be performed within the depth-first search of GRaSP.
setNonSingularDepth(int) - Method in class edu.cmu.tetrad.search.GraspFci
Sets depth for non-singular tucks.
setNonSingularDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Setter for the field nonSingularDepth.
setNparents(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Sets the number of parents.
setNumberFormat(NumberFormat) - Method in class edu.cmu.tetrad.data.BoxDataSet
The number formatter used to print out continuous values.
setNumberFormat(NumberFormat) - Method in interface edu.cmu.tetrad.data.DataSet
The number formatter used to print out continuous values.
setNumberFormat(NumberFormat) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
The number formatter used to print out continuous values.
setNumberFormat(NumberFormat) - Method in class edu.cmu.tetrad.util.NumberFormatUtil
Sets the number format, nf.
setNumBins(int) - Method in class edu.cmu.tetrad.data.Histogram
For a continuous target, sets the number of bins for the histogram.
setNumBootstraps(int) - Method in class edu.cmu.tetrad.search.test.Kci
Sets the number of bootstraps to do.
setNumBscBootstrapSamples(int) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Sets the number of bootstrap samples.
setNumCategories(Node, int) - Method in class edu.cmu.tetrad.bayes.BayesPm
Sets the number of values for the given node to the given number.
setNumCategoriesToDiscretize(int) - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianLikelihood
Sets the number of categories to use to discretize child variables to avoid integration
setNumCategoriesToDiscretize(int) - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianScore
Sets tne number of categories used to discretize, when this optimization is used.
setNumCategoriesToDiscretize(int) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Sets the number of categories used to discretize variables.
setNumCellsPerDish(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets the number of cells per dish.
setNumCellsPerDish(int) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setNumCellsPerDish.
setNumClusters(int) - Method in class edu.cmu.tetrad.data.Clusters
Sets the number of clusters represented, or -1 if the number is allowed to vary.
setNumCPDAGsToStore(int) - Method in class edu.cmu.tetrad.search.SvarFges
Sets the number of patterns to store.
setNumDishes(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets the number of dishes that are to be simulated.
setNumDishes(int) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setNumDishes.
setNumEdges(int) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field numEdges.
setNumEdges1(int) - Method in class edu.cmu.tetrad.simulation.GdistanceRandom
Setter for the field numEdges1.
setNumEdges2(int) - Method in class edu.cmu.tetrad.simulation.GdistanceRandom
Setter for the field numEdges2.
setNumExpansions(int) - Method in class edu.cmu.tetrad.search.FgesMb
Sets the number of expansions for a given object.
setNumFactors(int) - Method in class edu.cmu.tetrad.search.FactorAnalysis
Sets the number of factors to find.
setNumFunctions(int) - Method in class edu.cmu.tetrad.search.test.ConditionalCorrelationIndependence
Sets the number of functions used in the ConditionalCorrelationIndependence analysis.
setNumInitialLags(int) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Setter for the field numInitialLags.
setNumIterations(int) - Method in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Sets the number of iterations for the Markov chain process.
setNumIterations(int) - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbsParams
Setter for the field numIterations.
setNumNodes(int) - Method in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Sets the number of nodes and resets all of the other parameters to default values accordingly.
setNumRandomizedSearchModels(int) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.PagSamplingRfci
Set the number of randomized search models.
setNumRandomizedSearchModels(int) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Sets the number of randomized search models.
setNumRestarts(int) - Method in class edu.cmu.tetrad.sem.SemEstimator
Setter for the field numRestarts.
setNumRestarts(int) - Method in interface edu.cmu.tetrad.sem.SemOptimizer
setNumRestarts.
setNumRestarts(int) - Method in class edu.cmu.tetrad.sem.SemOptimizerEm
setNumRestarts.
setNumRestarts(int) - Method in class edu.cmu.tetrad.sem.SemOptimizerPowell
setNumRestarts.
setNumRestarts(int) - Method in class edu.cmu.tetrad.sem.SemOptimizerRegression
setNumRestarts.
setNumRestarts(int) - Method in class edu.cmu.tetrad.sem.SemOptimizerRicf
setNumRestarts.
setNumRestarts(int) - Method in class edu.cmu.tetrad.sem.SemOptimizerScattershot
setNumRestarts.
setNumSamplesPerDish(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets the number of samples that will be generated in the measured data for each dish.
setNumSamplesPerDish(int) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setNumSamplesPerDish.
setNumStarts(int) - Method in class edu.cmu.tetrad.search.BFci
Returns the number of times to restart the search.
setNumStarts(int) - Method in class edu.cmu.tetrad.search.Boss
Sets the number of random starts to use.
setNumStarts(int) - Method in class edu.cmu.tetrad.search.Grasp
Sets the number of times the best order algorithm should be rerun with different starting permutations in search of a best BIC scoring permutation.
setNumStarts(int) - Method in class edu.cmu.tetrad.search.GraspFci
Sets the number of starts for GRaSP.
setNumStarts(int) - Method in class edu.cmu.tetrad.search.LvDumb
Sets the number of starts for BOSS.
setNumStarts(int) - Method in class edu.cmu.tetrad.search.LvLite
Sets the number of starts for BOSS.
setNumStarts(int) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Setter for the field numStarts.
setNumSubsamples(int) - Method in class edu.cmu.tetrad.search.Cstar
Sets the number of subsamples.
setNumThreads(int) - Method in class edu.cmu.tetrad.search.BFci
Sets the number of threads to use.
setNumThreads(int) - Method in class edu.cmu.tetrad.search.Boss
Sets the number of threads to use.
setNumThreads(int) - Method in class edu.cmu.tetrad.search.Fges
Sets the number of threads to use.
setNumThreads(int) - Method in class edu.cmu.tetrad.search.GFci
Sets the number of threads to use in the search.
setNumVars(int) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field numVars.
setObject(int, int, Object) - Method in class edu.cmu.tetrad.data.BoxDataSet
Sets the value at the given (row, column) to the given value.
setObject(int, int, Object) - Method in interface edu.cmu.tetrad.data.DataSet
Sets the value at the given (row, column) to the given value.
setObject(int, int, Object) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Sets the value at the given (row, column) to the given value.
setOneEdgeFaithfulnessAssumed(boolean) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field oneEdgeFaithfulnessAssumed.
setOnlyCanCauseNextTier(int, boolean) - Method in class edu.cmu.tetrad.data.Knowledge
setOnlyCanCauseNextTier.
setOrder(List<Node>) - Method in class edu.cmu.tetrad.search.PermutationSearch
Sets the order list for the search.
setOrder(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Sets the order.
setOrder(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Sets the order.
setOrder(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Sets the order.
setOrdered(boolean) - Method in class edu.cmu.tetrad.search.Grasp
True if GRasP0 should be performed before GRaSP1 and GRaSP1 before GRaSP2.
setOrdered(boolean) - Method in class edu.cmu.tetrad.search.GraspFci
Sets whether to use the ordered version of GRaSP.
setOrdered(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Setter for the field ordered.
setOrientationAlpha(double) - Method in class edu.cmu.tetrad.search.FaskOrig
Sets the orientation alpha.
setOrientStrongerDirection(boolean) - Method in class edu.cmu.tetrad.search.Lofs
Sets whether orientation should be done in the stronger direction, where applicable.
setOut(OutputStream) - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
Setter for the field out.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.Fas
Sets the PrintStream to be used for output.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.Fasd
Sets the output stream for this object.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.Fges
Sets the output stream that output (except for log output) should be sent to.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.FgesMb
Sets the output stream that output (except for log output) should be sent to.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.GFci
Sets the print stream used for output, default System.out.
setOut(PrintStream) - Method in interface edu.cmu.tetrad.search.IFas
sets the print stream to send text to.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.SpFci
Sets the output stream used to print.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.SvarFas
Sets the output stream for printing.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.SvarFges
Sets the output stream that output (except for log output) should be sent to.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Sets the output stream that output (except for log output) should be sent to.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.work_in_progress.FasFdr
sets the print stream to send text to.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Sets the PrintStream object used for output by the IGFci instance.
setOut(PrintStream) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Sets the output stream for this instance.
setOut(PrintStream) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Setter for the field out.
setOut(PrintStream) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Sets the output stream that output (except for log output) should be sent to.
setOut(String, int, int, int, int, String, int, double, double, String) - Method in class edu.cmu.tetrad.calibration.DataForCalibrationRfci
setOut.
setOutputDelimiter(Character) - Method in class edu.cmu.tetrad.data.BoxDataSet
The character used a delimiter when the dataset is output
setOutputDelimiter(Character) - Method in interface edu.cmu.tetrad.data.DataSet
The character used a delimiter when the dataset is output
setOutputDelimiter(Character) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
The character used a delimiter when the dataset is output
setOutputRBD(boolean) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Sets whether the output should be RBD.
setOutputs(int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Setter for the field outputs.
setPag(boolean) - Method in class edu.cmu.tetrad.search.test.MsepTest
True iff the graph is a PAG
setPag(Graph) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Sets the PAG (partial ancestral graph) for the strategy.
setParallel(boolean) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Sets whether the discriminating path orientation should be run in parallel.
setParallelism(int) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Sets the number of threads to be used for parallel processing.
setParallelism(int) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Sets the level of parallelism for the ForkJoinPool by specifying the number of processors to be used.
setParallelized(boolean) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
Setter for the field parallelized.
setParallelized(boolean) - Method in class edu.cmu.tetrad.search.Cstar
Sets whether the algorithm should be parallelized.
setParallelized(boolean) - Method in class edu.cmu.tetrad.search.FgesMb
Sets the parallelized flag of the object.
setParallelized(boolean) - Method in class edu.cmu.tetrad.search.MarkovCheck
True if the checks should be parallelized.
setParamComparison(Parameter, Parameter, ParamComparison) - Method in class edu.cmu.tetrad.sem.SemPm
Sets the comparison of parameter a to parameter b.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.Beta
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.ChiSquare
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.Discrete
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in interface edu.cmu.tetrad.util.dist.Distribution
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.Exponential
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.Gamma
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.GaussianPower
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.Indicator
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.LogNormal
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.MixtureOfGaussians
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.Normal
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.Poisson
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.SingleValue
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.Split
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.TruncatedNormal
Sets the index'th parameter to the given value.
setParameter(int, double) - Method in class edu.cmu.tetrad.util.dist.Uniform
Sets the index'th parameter to the given value.
setParameterBoundsEnforced(boolean) - Method in interface edu.cmu.tetrad.sem.ISemIm
setParameterBoundsEnforced.
setParameterBoundsEnforced(boolean) - Method in class edu.cmu.tetrad.sem.SemIm
setParameterBoundsEnforced.
setParameterEstimationInitializationExpression(String, String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Sets the parameter estimation initialization expression for the given parameter.
setParameterEstimationInitializationExpression(String, String, String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Sets the expression which should be evaluated when calculating new values for the given parameter.
setParameterExpression(String, String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Sets the expression which should be evaluated when calculating new values for the given parameter.
setParameterExpression(String, String, String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Sets the expression which should be evaluated when calculating new values for the given parameter.
setParametersEstimationInitializationTemplate(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Sets the template for parameter estimation initialization.
setParametersTemplate(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Sets the parameter template for the object.
setParameterValue(Edge, double) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
setParameterValue.
setParameterValue(String, double) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
setParameterValue.
setParamName(String) - Method in class edu.cmu.tetrad.util.ParamDescription
Setter for the field paramName.
setParams(Parameters) - Method in class edu.cmu.tetrad.sem.SemIm
Setter for the field params.
setParams(Mgm.MGMParams) - Method in class edu.pitt.csb.mgm.Mgm
Setter for the field params.
setParamValue(Node, Node, double) - Method in interface edu.cmu.tetrad.sem.ISemIm
setParamValue.
setParamValue(Node, Node, double) - Method in class edu.cmu.tetrad.sem.SemIm
setParamValue.
setParamValue(Parameter, double) - Method in interface edu.cmu.tetrad.sem.ISemIm
setParamValue.
setParamValue(Parameter, double) - Method in class edu.cmu.tetrad.sem.SemIm
Sets the value of a parameter in the model.
setParents(NbComponent[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Sets the parents.
setPath(String) - Method in class edu.cmu.tetrad.algcomparison.algorithm.ExternalAlgorithm
Setter for the field path.
setPcHeuristicType(PcCommon.PcHeuristicType) - Method in class edu.cmu.tetrad.search.Cpc
Sets the PC heuristic type.
setPcHeuristicType(PcCommon.PcHeuristicType) - Method in class edu.cmu.tetrad.search.Fas
Sets the type of heuristic to be used in the PC algorithm.
setPcHeuristicType(PcCommon.PcHeuristicType) - Method in class edu.cmu.tetrad.search.Fci
Sets which PC heuristic type should be used in the initial adjacency search.
setPcHeuristicType(PcCommon.PcHeuristicType) - Method in class edu.cmu.tetrad.search.FciMax
Sets the FAS heuristic from PC used in search.
setPcHeuristicType(PcCommon.PcHeuristicType) - Method in class edu.cmu.tetrad.search.Pc
Sets the PC heuristic type.
setPcHeuristicType(PcCommon.PcHeuristicType) - Method in class edu.cmu.tetrad.search.utils.PcCommon
Setter for the field pcHeuristicType.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.Mimbuild
Sets the penalty discount of the score used to infer the structure graph.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.score.BasisFunctionBicScore
Sets the penalty discount value, which is used to adjust the penalty term in the BIC score calculation.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianScore
Sets the penalty discount for this score, which is a multiplier on the penalty discount of the BIC score.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.score.DegenerateGaussianScore
Sets the penalty discount.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
Sets the penalty discount, which is a multiplier on the penalty term of BIC.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
Sets the penalty discount, which is a multiplier on the penalty term of BIC.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.score.GicScores
Sets the penalty discount.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Sets the multiplier on the penalty term for this score.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
For BIC score, a multiplier on the penalty term.
setPenaltyDiscount(double) - Method in interface edu.cmu.tetrad.search.utils.HasPenaltyDiscount
setPenaltyDiscount.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.work_in_progress.FasLofs
Setter for the field penaltyDiscount.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Sets the penalty discount.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
Seets the penalty discount.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
Seets the penalty discount.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
Seets the penalty discount.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Setter for the field penaltyDiscount.
setPenaltyDiscount(double) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field penaltyDiscount.
setPercent(double) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Sets the percentage value.
setPercentResample(double) - Method in class edu.cmu.tetrad.search.MarkovCheck
Sets the percentage of all samples to use when resampling for each conditional independence test.
setPercentUnregulated(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Setter for the field percentUnregulated.
setPerms(int) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Set the number of bootstrap samples to use
setPerms(int) - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Set the number of bootstrap samples to use
setPixelDigitalization(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets the pixel digitalization error.
setPixelDigitalization(double) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setPixelDigitalization.
setPolyConst(double) - Method in class edu.cmu.tetrad.search.test.Kci
Sets the constant of the polynomial kernel, if used
setPolyDegree(double) - Method in class edu.cmu.tetrad.search.test.Kci
Sets the degree of the polynomial kernel, if used
setPolynomial(int, Polynomial) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialFunction
Sets the polynomial for the given factor.
setPopulationGraph(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Sets the population graph for the current instance.
setPossibleDsepSearchDone(boolean) - Method in class edu.cmu.tetrad.search.Fci
Sets whether the (time-consuming) possible msep step should be done.
setPossibleMsepSearchDone(boolean) - Method in class edu.cmu.tetrad.search.Cfci
Whether to do the discriminating path rule.
setPossibleMsepSearchDone(boolean) - Method in class edu.cmu.tetrad.search.FciMax
Sets whether the (time-consuming) possible msep step should be done.
setPower(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Sets the power.
setPrecomputeCovariances(boolean) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicDiff
Returns the precompute covariances flag.
setPrecomputeCovariances(boolean) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicDiffPerRecord
Returns true if the covariances are precomputed.
setPrecomputeCovariances(boolean) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicEst
Returns the precompute covariances flag.
setPrecomputeCovariances(boolean) - Method in class edu.cmu.tetrad.algcomparison.statistic.BicTrue
Returns whether to precompute covariances.
setPrecomputeCovariances(boolean) - Method in class edu.cmu.tetrad.calibration.DataForCalibrationRfci
Setter for the field precomputeCovariances.
setPrecomputeCovariances(boolean) - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
Setter for the field precomputeCovariances.
setPreferLinear(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
Setter for the field preferLinear.
setPriorCount(double) - Method in class edu.cmu.tetrad.bayes.CptMapCounts
Sets the prior count for all cells in the CptMapCounts.
setPriorEqivalentSampleSize(double) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCInference
Sets the prior equivalent sample size.
setPriorEquivalentSampleSize(double) - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Sets the prior equivalent sample size for the independence test.
setPriorEquivalentSampleSize(double) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.PagSamplingRfci
Set the prior equivalent sample size.
setProbability(double) - Method in class edu.cmu.tetrad.graph.Edge
Setter for the field probability.
setProbability(double) - Method in class edu.cmu.tetrad.graph.EdgeTypeProbability
Setter for the field probability.
setProbability(int, double) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
setProbability.
setProbability(int, double[][]) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Sets the probability for the given node.
setProbability(int, double[][]) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Sets the probability for the given node.
setProbability(int, double[][]) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Sets the probability for the given node.
setProbability(int, double[][]) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Sets the probability for the given node.
setProbability(int, double[][]) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
setProbability.
setProbability(int, int, int, double) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Sets the probability for the given node at a given row and column in the table for that node.
setProbability(int, int, int, double) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Sets the probability for the given node at a given row and column in the table for that node.
setProbability(int, int, int, double) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Sets the probability value for a specific node, row, and column in the probability table.
setProbability(int, int, int, double) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Sets the probability for the given node at a given row and column in the table for that node.
setProbability(int, int, int, double) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Sets the probability for the given node at a given row and column in the table for that node.
setPseudocount(int, int, int, double) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
setPseudocount.
setQuoteSensitive(boolean) - Method in class edu.cmu.tetrad.data.RegexTokenizer
True iff the parser should be aware of quotation marks and remove them from returned strings.
setR2Orient2Cycles(boolean) - Method in class edu.cmu.tetrad.search.Lofs
Sets for R2 whether cycles should be oriented.
setRandomlyInitialized(boolean) - Method in class edu.cmu.tetrad.graph.LayoutUtil.KamadaKawaiLayout
Sets whether the spring layout should start from a randomlyInitialized position or from the getModel positions of the nodes.
setRawDataSaved(boolean) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets whether the raw data that is generated should be saved beyond what's needed for the getModel cell being simulated.
setRawDataSaved(boolean) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setRawDataSaved.
setRecursionDepth(int) - Method in class edu.cmu.tetrad.search.LvLite
Sets the depth of the GRaSP if it is used.
setRegularizer(double) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Sets the regularizer.
setRequired(String, String) - Method in class edu.cmu.tetrad.data.Knowledge
Marks the edge var1 --> var2 as required.
setResetAfterBM(boolean) - Method in class edu.cmu.tetrad.search.Boss
Sets whether the grow-shrink trees should be reset after each best-mutation step.
setResetAfterRS(boolean) - Method in class edu.cmu.tetrad.search.Boss
Sets whether the grow-shrink trees should be reset after each restart.
setResolveAlmostCyclicPaths(boolean) - Method in class edu.cmu.tetrad.search.SvarFci
Sets whether almost cyclic paths should be resolved during the search.
setResolveAlmostCyclicPaths(boolean) - Method in class edu.cmu.tetrad.search.SvarGfci
Sets whether to resolve almost cyclic paths during the search.
setResultGraph(Graph) - Method in class edu.cmu.tetrad.study.performance.ComparisonResult
Setter for the field resultGraph.
setResultType(ComparisonParameters.ResultType) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field resultType.
setRevertToUnshieldedColliders(boolean) - Method in class edu.cmu.tetrad.search.utils.MeekRules
Sets whether orientations in the graph should be reverted to its unshielded colliders before performing any Meek rule orientations.
setRhoAllEqual(double) - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
setRhoAllEqual.
setRiskBound(double) - Method in class edu.cmu.tetrad.search.score.ZsbScore
Sets the risk bound for the Zhang Shen Bound score.
setRowNorm(boolean) - Method in class edu.cmu.tetrad.search.FastIca
A logical value indicating whether rows of the data matrix 'X' should be standardized beforehand.
setRows(int[]) - Method in class edu.cmu.tetrad.regression.LogisticRegression
Setter for the field rows.
setRows(int[]) - Method in class edu.cmu.tetrad.regression.RegressionDataset
Setter for the field rows.
setRows(List<Integer>) - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianLikelihood
Sets the rows to be used in the table.
setRows(List<Integer>) - Method in class edu.cmu.tetrad.search.test.ConditionalCorrelationIndependence
Sets the list of row indices
setRows(List<Integer>) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Sets the rows to use for the test.
setRows(List<Integer>) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalCorrelation
Sets the rows to use for the test.
setRows(List<Integer>) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Allows the user to set which rows are used in the test.
setRows(List<Integer>) - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Allows the user to set which rows are used in the test.
setRows(List<Integer>) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Allows the user to set which rows are used in the test.
setRows(List<Integer>) - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Sets the list of rows to use for the test.
setRows(List<Integer>) - Method in class edu.cmu.tetrad.search.test.Kci
Allows the user to set which rows are used in the test.
setRows(List<Integer>) - Method in interface edu.cmu.tetrad.search.test.RowsSettable
Sets the rows to use for the test.
setRule(Lofs.Rule) - Method in class edu.cmu.tetrad.search.Lofs
Sets the rule to use to do the orientation.
setRuleType(GicScores.RuleType) - Method in class edu.cmu.tetrad.search.score.GicScores
Sets the rule type.
setRuleType(SemBicScore.RuleType) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Sets the rule type to use.
setSamplePrior(double) - Method in class edu.cmu.tetrad.search.score.BdeScore
Sets the sample prior for the BDe score.
setSamplePrior(double) - Method in class edu.cmu.tetrad.search.score.BdeuScore
Sets the sample prior for the BdeuScore object.
setSamplePrior(double) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
Sets the sample prior.
setSamplePrior(double) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
Sets the sample prior.
setSamplePrior(double) - Method in interface edu.cmu.tetrad.search.score.DiscreteScore
Sets the sample prior.
setSamplePrior(double) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
For BDeu score for discrete search; see Chickering (2002).
setSamplePrior(double) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Sets the value for the samplePrior field.
setSamplePrior(double) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Sets the value of the sample prior.
setSamplePrior(double) - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Sets the prior probability value assigned to the sample.
setSamplePrior(double) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field samplePrior.
setSampleSampleVariability(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets the sample to sample variability.
setSampleSampleVariability(double) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setSampleSampleVariability.
setSampleSize(int) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Sets the sample size used in the covariance matrix.
setSampleSize(int) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Sets the sample size used in the covariance matrix.
setSampleSize(int) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Sets the sample size used in the covariance matrix.
setSampleSize(int) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Sets the sample size used in the covariance matrix.
setSampleSize(int) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field sampleSize.
setSampleStyle(Cstar.SampleStyle) - Method in class edu.cmu.tetrad.search.Cstar
Sets the sample style.
setSaveCPDAGs(boolean) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Sets whether to save CPDAGs.
setSaveCPDAGs(boolean) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
Setter for the field saveCPDAGs.
setSaveData(boolean) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Sets the flag indicating whether to save data.
setSaveGraphs(boolean) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Sets whether to save graphs.
setSaveGraphs(boolean) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
Setter for the field saveGraphs.
setSavePags(boolean) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Sets the value of 'savePags' flag.
setSavePags(boolean) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
Setter for the field savePags.
setScalingFactor(double) - Method in class edu.cmu.tetrad.search.test.ConditionalCorrelationIndependence
Sets the bandwidth adjustment value for the ConditionalCorrelationIndependence analysis.
setScalingFactor(double) - Method in class edu.cmu.tetrad.search.test.Kci
Sets the width multiplier.
setScore(Lofs.Score) - Method in class edu.cmu.tetrad.search.Lofs
Sets the (LoFS) score to use.
setScore(ScoreType) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field score.
setScoreType(ScoreType) - Method in class edu.cmu.tetrad.sem.SemEstimator
Setter for the field scoreType.
setScoreType(ScoreType) - Method in class edu.cmu.tetrad.sem.SemIm
Setter for the field scoreType.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.DirectLingam
Sets the score wrapper for this DirectLingam instance.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask
Sets the score wrapper for the object.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig
Sets the score wrapper for the object.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated
Sets a score wrapper if not null.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskLofsConcatenated
Sets a score wrapper if not null.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote
Sets a score wrapper if not null.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod
Sets a score wrapper if not null.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated
Sets a score wrapper if not null.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.Images
Sets the score wrapper for the algorithm.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss
Sets a score wrapper if not null.
setScoreWrapper(ScoreWrapper) - Method in interface edu.cmu.tetrad.algcomparison.algorithm.MultiDataSetAlgorithm
Sets a score wrapper if not null.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Boss
Sets the score wrapper.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossLingam
Sets the score wrapper.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar
Sets the score wrapper.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges
Sets the score wrapper.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMb
Sets the score wrapper.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp
Sets the score wrapper.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.RestrictedBoss
Sets the score wrapper.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Sp
Sets the score wrapper.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci
Sets the score wrapper for this algorithm.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossDumb
Sets the score wrapper for the algorithm.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPag
Sets the score wrapper for the algorithm.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci
Sets the score wrapper for the algorithm.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci
Sets the score wrapper for the algorithm.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvLite
Sets the score wrapper for the algorithm.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Sets the ScoreWrapper object for the algorithm.
setScoreWrapper(ScoreWrapper) - Method in class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Sets the score wrapper for the algorithm.
setScoreWrapper(ScoreWrapper) - Method in interface edu.cmu.tetrad.algcomparison.utils.UsesScoreWrapper
Sets the score wrapper.
setSd(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Sets the standard deviation.
setSeed(long) - Method in class edu.cmu.tetrad.search.BFci
Sets the seed for the random number generator.
setSeed(long) - Method in class edu.cmu.tetrad.search.FaskOrig
Sets the seed for generating random numbers.
setSeed(long) - Method in class edu.cmu.tetrad.search.Grasp
Sets the seed for random number generation.
setSeed(long) - Method in class edu.cmu.tetrad.search.GraspFci
Setter for the field seed.
setSeed(long) - Method in class edu.cmu.tetrad.search.Mimbuild
Setter for the field seed.
setSeed(long) - Method in class edu.cmu.tetrad.search.PermutationSearch
Sets the seed value used for generating random numbers.
setSeed(long) - Method in class edu.cmu.tetrad.util.RandomUtil
Sets the seed to the given value.
setSelected(Node, boolean) - Method in class edu.cmu.tetrad.data.BoxDataSet
Marks the given column as selected if 'selected' is true or deselected if 'selected' is false.
setSelected(Node, boolean) - Method in interface edu.cmu.tetrad.data.DataSet
Marks the given column as selected if 'selected' is true or deselected if 'selected' is false.
setSelected(Node, boolean) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Marks the given column as selected if 'selected' is true or deselected if 'selected' is false.
setSelectedModel(DataModel) - Method in class edu.cmu.tetrad.data.DataModelList
Setter for the field selectedModel.
setSelectionAlpha(double) - Method in class edu.cmu.tetrad.search.Cstar
Sets the selection alpha.
setSelectionBias(boolean) - Method in class edu.cmu.tetrad.data.AbstractVariable
Sets the selection bias status for this node.
setSelectionBias(boolean) - Method in class edu.cmu.tetrad.data.DiscreteVariable
 
setSelectionBias(boolean) - Method in class edu.cmu.tetrad.graph.GraphNode
Sets whether the node is selected as a bias node.
setSelectionBias(boolean) - Method in interface edu.cmu.tetrad.graph.Node
Returns the selection bias status for this node.
setSelfLoopCoef(double) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Setter for the field selfLoopCoef.
setSelfLoopStrength(double) - Method in class edu.cmu.tetrad.search.Lofs
Sets the self-loop strength, if applicable.
setSemIm(SemIm) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Setter for the field semIm.
setSemIm(SemIm) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Setter for the field semIm.
setSemOptimizer(SemOptimizer) - Method in class edu.cmu.tetrad.sem.SemEstimator
Setter for the field semOptimizer.
setSemPm(SemPm) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Setter for the field semPm.
setSemPm(SemPm) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Setter for the field semPm.
setSepsetFinderMethod(int) - Method in class edu.cmu.tetrad.search.BFci
Sets the method to be used for finding the sepset.
setSepsetFinderMethod(int) - Method in class edu.cmu.tetrad.search.GFci
Sets the method used to find the sepset in the GFci algorithm.
setSepsetFinderMethod(int) - Method in class edu.cmu.tetrad.search.GraspFci
Sets the method for finding sepsets in the GraspFci class.
setSepsetFinderMethod(int) - Method in class edu.cmu.tetrad.search.SpFci
Sets the method to use for finding sepsets, 1 = greedy, 2 = min-p., 3 = max-p, default min-p.
setSetAlgorithmKnowledge(boolean) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Sets the algorithm knowledge flag.
setSetType(ConditioningSetType) - Method in class edu.cmu.tetrad.search.MarkovCheck
Sets the type of conditioning sets to use in the Markov check.
setShortDescription(String) - Method in class edu.cmu.tetrad.util.ParamDescription
Setter for the field shortDescription.
setShowErrorTerms(boolean) - Method in class edu.cmu.tetrad.graph.SemGraph
Setter for the field showErrorTerms.
setShowUtilities(boolean) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Sets the value of the showUtilities property.
setShowUtilities(boolean) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
Setter for the field showUtilities.
setSignificance(double) - Method in interface edu.cmu.tetrad.search.utils.TetradTest
setSignificance.
setSignificance(double) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
setSignificance.
setSignificance(double) - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
setSignificance.
setSignificance(double) - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
setSignificance.
setSignificanceChecked(boolean) - Method in class edu.cmu.tetrad.search.Fofc
Sets whether the significance of the cluster should be checked for each cluster.
setSimIndex(int) - Method in class edu.cmu.tetrad.algcomparison.algorithm.ExternalAlgorithm
Setter for the field simIndex.
setSimulation(Simulation) - Method in class edu.cmu.tetrad.algcomparison.algorithm.ExternalAlgorithm
Setter for the field simulation.
setSingularDepth(int) - Method in class edu.cmu.tetrad.search.GraspFci
Sets depth for singular tucks.
setSkewEdgeThreshold(double) - Method in class edu.cmu.tetrad.search.FaskOrig
Sets the skew-edge threshold.
setSortByUtility(boolean) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Set the flag to determine if utility should do the sorting.
setSortByUtility(boolean) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
Setter for the field sortByUtility.
setSpringConstant(double) - Method in class edu.cmu.tetrad.graph.LayoutUtil.KamadaKawaiLayout
Sets the spring constant; higher for more elasticity.
setStable(boolean) - Method in class edu.cmu.tetrad.search.Cpc
Sets whether the stable adjacency search should be used.
setStable(boolean) - Method in class edu.cmu.tetrad.search.Fas
Sets whether the stable adjacency search should be used.
setStable(boolean) - Method in class edu.cmu.tetrad.search.Fci
Sets whether the stable options should be used in the initial adjacency search.
setStable(boolean) - Method in class edu.cmu.tetrad.search.FciMax
Sets whether the stable option will be used for search.
setStable(boolean) - Method in class edu.cmu.tetrad.search.Pc
Sets whether the stable adjacency search should be used.
setStartIm(SemIm) - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbsParams
Setter for the field startIm.
setStartingValue(double) - Method in class edu.cmu.tetrad.sem.Parameter
Sets the starting value in case this is a fixed parameter.
setStartsWith(String, String, GeneralizedSemPm) - Static method in class edu.pitt.csb.mgm.MixedUtils
Set all existing parameters that begins with sta to template and also set template for any new parameters
setStartsWithParametersEstimationInitializationTemplate(String, String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Sets the parameter estimation initialization template for a given startsWith string.
setStartsWithParametersTemplate(String, String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Sets the parameter template for expressions that start with the specified string.
setStartWith(LvLite.START_WITH) - Method in class edu.cmu.tetrad.search.LvLite
Sets the algorithm to use to obtain the initial CPDAG.
setStdout(PrintStream) - Method in class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs
Setter for the field stdout.
setStepsGenerated(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Sets the number of time steps to generate.
setStepsGenerated(int) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
setStepsGenerated.
setStopEnergy(double) - Method in class edu.cmu.tetrad.graph.LayoutUtil.KamadaKawaiLayout
Sets the max delta at which the algorithm will stop settling.
setStretch(double) - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbsParams
Setter for the field stretch.
setStructurePrior(double) - Method in class edu.cmu.tetrad.search.score.BdeScore
Sets the structure prior for the BDe score.
setStructurePrior(double) - Method in class edu.cmu.tetrad.search.score.BdeuScore
Sets the structure prior for the BdeuScore object.
setStructurePrior(double) - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianScore
Setter for the field structurePrior.
setStructurePrior(double) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
Sets the structure prior.
setStructurePrior(double) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
Sets the structure prior.
setStructurePrior(double) - Method in interface edu.cmu.tetrad.search.score.DiscreteScore
Sets the structure prior.
setStructurePrior(double) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Sets the structure prior for this score.
setStructurePrior(double) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
For BDeu score for discrete search; see Chickering (2002).
setStructurePrior(double) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Sets the structure prior for the model.
setStructurePrior(double) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Sets the structure prior value for the current configuration.
setStructurePrior(double) - Method in interface edu.cmu.tetrad.search.work_in_progress.ISScore
Sets the prior value assigned to the structure.
setStructurePrior(double) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field structurePrior.
setSubstitutions(Map<String, Double>) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
setSubstitutions.
setSymmetricFirstStep(boolean) - Method in class edu.cmu.tetrad.search.Fges
Sets whether the first step of the procedure will score both X->Y and Y->X and prefer the higher score (for adding X--Y to the graph).
setSymmetricFirstStep(boolean) - Method in class edu.cmu.tetrad.search.FgesMb
Sets whether the first step of the procedure will score both X->Y and Y->X and prefer the higher score (for adding X--Y to the graph).
setSymmetricFirstStep(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Sets whether the first step of the algorithm should be symmetric.
setTabDelimitedTables(boolean) - Method in class edu.cmu.tetrad.algcomparison.Comparison
Sets the flag indicating whether tab-delimited tables should be used.
setTabDelimitedTables(boolean) - Method in class edu.cmu.tetrad.algcomparison.TimeoutComparison
Setter for the field tabDelimitedTables.
setTarget(String) - Method in class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete
Sets the target variable.
setTestTimeout(long) - Method in class edu.cmu.tetrad.search.LvLite
Sets the timeout for the testing steps, for the extra edge removal steps and the discriminating path steps.
setTestTimeout(long) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Sets the timeout for running tests.
setTestType(BpcTestType) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
setTestType.
setTetradLoggerConfig(TetradLoggerConfig) - Method in class edu.cmu.tetrad.util.TetradLogger
Sets what configuration should be used to determine which events to log.
setThr(double) - Method in class edu.cmu.tetrad.search.work_in_progress.Glasso
Setter for the field thr.
setThreshold(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Sets whether the independence test should be thresholded (true) or randomized (false).
setThreshold(boolean) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.PagSamplingRfci
Set the threshold.
setThreshold(double) - Method in class edu.cmu.tetrad.search.FactorAnalysis
Sets the threshold.
setThreshold(double) - Method in class edu.cmu.tetrad.search.test.Kci
Sets the threshold.
setThresholdNoRandomConstrainSearch(boolean) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Setter for the field thresholdNoRandomConstrainSearch.
setThresholdNoRandomDataSearch(boolean) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Setter for the field thresholdNoRandomDataSearch.
setTier(int, List<String>) - Method in class edu.cmu.tetrad.data.Knowledge
Sets the variable in a given tier to the specified list.
setTierForbiddenWithin(int, boolean) - Method in class edu.cmu.tetrad.data.Knowledge
Forbids any variable from being parent of any other variable within the given tier, or cancels this forbidding.
setTNeighbors(Set<Node>) - Method in class edu.cmu.tetrad.search.utils.Bes.Arrow
Sets the set of nodes that are in TNeighbors.
setToken(int, int, String) - Method in class edu.cmu.tetrad.util.TextTable
Sets the token at the given row and column, each of which must be >= 0 and less than the number of rows or columns, respectively.
setTolerance(double) - Method in class edu.cmu.tetrad.search.FastIca
Sets a positive scalar giving the tolerance at which the un-mixing matrix is considered to have converged.
setToleranceDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Setter for the field toleranceDepth.
setToTautology() - Method in class edu.cmu.tetrad.bayes.Proposition
Specifies that all variables in the proposition are either completely allowed (true) or completely disallowed (false) for all of their categories.
setTrial(int) - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
Setter for the field trial.
setTrimmingStyle(int) - Method in class edu.cmu.tetrad.search.FgesMb
Sets the trimming style for the algorithm.
setTrueDag(Graph) - Method in class edu.cmu.tetrad.study.performance.ComparisonResult
Setter for the field trueDag.
setTrueGraph(Graph) - Method in class edu.cmu.tetrad.search.SvarFges
Sets the true graph, which will result in some edges in output graphs being marked with asterisks.
setTrueGraph(Graph) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
If the true graph is set, askterisks will be printed in log output for the true edges.
setTrueGraph(Graph) - Method in interface edu.cmu.tetrad.search.utils.IPurify
setTrueGraph.
setTrueGraph(Graph) - Method in class edu.cmu.tetrad.search.utils.PurifyScoreBased
setTrueGraph.
setTrueGraph(Graph) - Method in class edu.cmu.tetrad.search.utils.PurifyTetradBased
setTrueGraph.
setTrueGraph(Graph) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Sets the true graph.
setTrueInputs(int[]) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
Setter for the field trueInputs.
setTruePag(Graph) - Method in class edu.cmu.tetrad.search.utils.TsDagToPag
Setter for the field truePag.
setTwoCycleScreeningCutoff(double) - Method in class edu.cmu.tetrad.search.FaskOrig
Sets the cutoff for two-cycle screening.
setType(ParamConstraintType) - Method in class edu.cmu.tetrad.sem.ParamConstraint
Setter for the field type.
setUncoveredDepth(int) - Method in class edu.cmu.tetrad.search.Grasp
Sets the maximum depth at which uncovered tucks can be performed within the depth-first search of GRaSP.
setUncoveredDepth(int) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Setter for the field uncoveredDepth.
setUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.Dag
Sets the underlined triples.
setUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
setUnderLineTriples.
setUnderLineTriples(Set<Triple>) - Method in interface edu.cmu.tetrad.graph.Graph
setUnderLineTriples.
setUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.LagGraph
setUnderLineTriples.
setUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.SemGraph
setUnderLineTriples.
setUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Sets the underline triples.
setUnderLineTriples(Set<Triple>) - Method in class edu.cmu.tetrad.graph.Underlines
Setter for the field underLineTriples.
setUp() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestSimpleRandomizer
Sets up a graph to randomize with 100 variables in it.
setUp() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.TestMeasurementSimulator
Sets up a GeneHistory object in the format for Richard's diagnostic.
setUpperBound(double) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Sets the upper bound.
setUpperBoundDouble(double) - Method in class edu.cmu.tetrad.util.ParamDescription
Setter for the field upperBoundDouble.
setUpperBoundInt(int) - Method in class edu.cmu.tetrad.util.ParamDescription
Setter for the field upperBoundInt.
setUpperBoundLong(long) - Method in class edu.cmu.tetrad.util.ParamDescription
Setter for the field upperBoundLong.
setUseBes(boolean) - Method in class edu.cmu.tetrad.search.Boss
Sets up BOSS to use the BES algorithm to render BOSS correct under the faithfulness assumption.
setUseBes(boolean) - Method in class edu.cmu.tetrad.search.LvDumb
Sets whether to use the BES (Backward Elimination Search) algorithm during the search.
setUseBes(boolean) - Method in class edu.cmu.tetrad.search.LvLite
Sets whether to use the BES (Backward Elimination Search) algorithm during the search.
setUseDataOrder(boolean) - Method in class edu.cmu.tetrad.search.Boss
True if the order of the variables in the data should be used for an initial best-order search, false if a random permutation should be used.
setUseDataOrder(boolean) - Method in class edu.cmu.tetrad.search.Grasp
True if the order of the variables in the data should be used for an initial best-order search, false if a random permutation should be used.
setUseDataOrder(boolean) - Method in class edu.cmu.tetrad.search.GraspFci
Sets whether to use data order for GRaSP (as opposed to random order) for the first step of GRaSP
setUseDataOrder(boolean) - Method in class edu.cmu.tetrad.search.LvDumb
Sets whether the search algorithm should use the order of the data set during the search.
setUseDataOrder(boolean) - Method in class edu.cmu.tetrad.search.LvLite
Sets the flag indicating whether to use data order.
setUseDataOrder(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Setter for the field useDataOrder.
setUseDisplayNames(boolean) - Method in class edu.cmu.tetrad.search.utils.BayesImParser
Sets whether to use display names.
setUseFasAdjacencies(boolean) - Method in class edu.cmu.tetrad.search.Fask
Sets the flag indicating whether to use Fast Adjacencies (FAS) for the search algorithm.
setUseFgES(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch
setUseFgES.
setUseHeuristic(boolean) - Method in class edu.cmu.tetrad.search.utils.MaxP
Sets whether the max P heuristic should be used.
setUseMaxPHeuristic(boolean) - Method in class edu.cmu.tetrad.search.Pc
Sets whether the max-p heuristic should be used for collider discovery.
setUsePseudoinverse(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Sets whether or not to use the pseudoinverse method for determining independence.
setUsePseudoInverse(boolean) - Method in class edu.cmu.tetrad.search.score.DegenerateGaussianScore
Sets the flag to indicate whether to use pseudo inverse in the score calculations.
setUsePseudoInverse(boolean) - Method in class edu.cmu.tetrad.search.score.EbicScore
Returns the gamma parameter for EBIC.
setUsePseudoInverse(boolean) - Method in class edu.cmu.tetrad.search.score.GicScores
Sets whether to use the pseudo-inverse when calculating the score.
setUsePseudoInverse(boolean) - Method in class edu.cmu.tetrad.search.score.PoissonPriorScore
Sets whether the pseudo-inverse should be used.
setUsePseudoInverse(boolean) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns the covariance matrix of the regression of the ith variable on its parents and the regression coefficients.
setUsePseudoInverse(boolean) - Method in class edu.cmu.tetrad.search.score.ZsbScore
Sets whether to use the pseudo-inverse in place of the inverse in the score.
setUseRaskuttiUhler(boolean) - Method in class edu.cmu.tetrad.search.Grasp
True if the Raskutti-Uhler method should be used, false if the Verma-Pearl method should be used.
setUseRaskuttiUhler(boolean) - Method in class edu.cmu.tetrad.search.GraspFci
Sets whether to use Raskutti and Uhler's modification of GRaSP.
setUseRaskuttiUhler(boolean) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Setter for the field useRaskuttiUhler.
setUseRaskuttiUhler(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
setUseRaskuttiUhler.
setUseScore(boolean) - Method in class edu.cmu.tetrad.search.Grasp
True if the score should be used (if both a score and a test are provided), false if not.
setUseScore(boolean) - Method in class edu.cmu.tetrad.search.GraspFci
Sets whether to use score for GRaSP (as opposed to independence test) for GRaSP.
setUseScore(boolean) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Setter for the field useScore.
setUseScore(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Setter for the field useScore.
setUseSkewAdjacencies(boolean) - Method in class edu.cmu.tetrad.search.Fask
Sets the flag indicating whether to use skew adjacencies in the FaskOrig class.
setValue(double) - Method in class edu.cmu.tetrad.sem.Mapping
Sets the value of the array element at the stored coordinates (i, j).
setValue(double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Sets the parents of this component.
setValue(double) - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbComponent
Sets the parents of this component.
setValue(int, boolean) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
Sets the boolean value in a given row of the table.
setValue(int, double) - Method in class edu.cmu.tetrad.sem.SemProposition
Sets the value at the specified index in the array of values.
setValue(int, int, double) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Sets the value of the covariance matrix at the specified indices.
setValue(int, int, double) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Sets the value of the covariance matrix at the specified indices.
setValue(int, int, double) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Sets the value of the covariance matrix at the specified indices.
setValue(int, int, double) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Sets the value of the covariance matrix at the specified indices.
setValue(int, int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrixF
Assigns double x to matrix element (r, c).
setValue(int, int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.MatrixF
Assigns double x to matrix element at (r, c).
setValue(int, int, double) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrixF
Sets the value of element (row,col) to x
setValue(int, int, float) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrixF
Assigns float x to matrix element (r, c)
setValue(int, int, float) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.MatrixF
Assigns float x to matrix element at (r, c)
setValue(int, int, float) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrixF
Assigns float x to matrix element (r, c)
setValue(int, int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrix
Assigns integer x to matrix element (r, c).
setValue(int, int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.Matrix
Assigns integer x to matrix element at (r, c).
setValue(int, int, int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrix
Sets the value of element (row,col) to x
setValue(int, int, short) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrix
Assigns short x to matrix element (r, c)
setValue(int, int, short) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.Matrix
Assigns short x to matrix element at (r, c)
setValue(int, int, short) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrix
Assigns short x to matrix element (r, c)
setValue(Node, double) - Method in class edu.cmu.tetrad.sem.SemProposition
Sets the value for a given node in the SemProposition object.
setVarHigh(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Setter for the field varHigh.
setVarHigh(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Setter for the field varHigh.
setVariable(int, boolean) - Method in class edu.cmu.tetrad.bayes.Proposition
Specifies that all categories for the given variable are either all allowed (true) or all disallowed (false).
setVariables(List<Node>) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Sets the list of Node variables for the covariance matrix.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Sets the list of Node variables for the covariance matrix.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Sets the list of Node variables for the covariance matrix.
setVariables(List<Node>) - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Sets the list of Node variables for the covariance matrix.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.PcMb
Setter for the field variables.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
Sets the variables to a new list of the same size.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
Sets the variables to a new list of the same size.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.score.GicScores
Sets the variables of the dataset.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Sets the variables of the covariance matrix.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Sets the variables to a new list of the same size.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Sets the varialbe to this list (of the same length).
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Setter for the field variables.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Sets the variables used in the independence test.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBDeuScore
Sets the list of variables after validating that each variable in the provided list has the same name as the corresponding variable in the existing list.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.ISBicScore
Sets the list of variables for the instance.
setVariables(List<Node>) - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Setter for the field variables.
setVariablesCopied(boolean) - Method in class edu.cmu.tetrad.data.Discretizer
Setter for the field variablesCopied.
setVariablesTemplate(String) - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Sets the variable template.
setVarLow(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation
Setter for the field varLow.
setVarLow(double) - Method in class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation
Setter for the field varLow.
setVarRange(double, double) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
setVarRange.
setVarsPerInd(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.LagGraphParams
Setter for the field varsPerInd.
setVarsPerInd(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraphParams
Sets the number of variables per individual.
setVerbose(boolean) - Method in class edu.cmu.tetrad.algcomparison.independence.Kci
Sets the verbosity level of the KCI test.
setVerbose(boolean) - Method in interface edu.cmu.tetrad.cluster.ClusteringAlgorithm
True iff verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.cluster.KMeans
True iff verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.BFci
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Boss
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Cfci
Whether verbose output (about independencies) is output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.CompositeIndependenceTest
Sets whether this test will print verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Cpc
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Cstar
Sets whether verbose output will be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Fas
Sets the verbose mode.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Fasd
Sets the verbose flag to control verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.FaskOrig
Sets the verbose mode.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.FastIca
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Fci
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.FciMax
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Fges
Sets whether verbose output should be produced.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.FgesMb
Sets whether verbose output should be produced.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Fofc
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Ftfc
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.GFci
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Grasp
Sets whether verbose output is printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.GraspFci
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.IcaLingam
A boolean indicating whether to print verbose output.
setVerbose(boolean) - Method in interface edu.cmu.tetrad.search.IFas
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in interface edu.cmu.tetrad.search.IndependenceTest
Sets whether this test will print verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.IndTestIod
Sets whether this test will print verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.LvDumb
Sets the verbosity level of the search algorithm.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.LvLite
Sets the verbosity level of the search algorithm.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Pc
Sets whether verbose output should be given.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Pcd
Sets whether this test will print verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.PcMb
Sets the verbosity level of the search.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.Rfci
Sets whether verbose output is printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.score.GicScores
Sets whether verbose output should be sent to out.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.score.IndTestScore
Sets whether verbose output should be sent to out.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Sets whether verbose output should be sent to out.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.SpFci
Sets whether verbose output is printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.SvarFas
Sets the verbosity of the program.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.SvarFci
Sets whether verbose output is to be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.SvarFges
Sets whether verbose output should be produced.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.SvarGfci
Sets whether verbose output is printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalCorrelation
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
Sets the verbose output flag.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Sets the verbose flag to enable or disable verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Sets the verbose mode for the IndTestHsic class.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestIndependenceFacts
Sets whether verbose output is to be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestMulti
Sets whether verbose output should be printed during the test.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestMvpLrt
Sets whether this test will print verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestProbabilistic
Sets the verbose flag indicating whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestRegression
Sets whether this test will print verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Sets the verbose output flag.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.Kci
Sets the verbosity of the method.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.MsepTest
Sets the verbosity level for the program.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Sets whether verbose output is enabled or not.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.Bes
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.BesPermutation
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.DagSepsets
Sets the verbose mode of the SepsetProducer.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.DagToPag
Setws whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.FciOrient
Sets whether verbose output is printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.FgesOrienter
Sets whether verbose output should be produced.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.MaxP
Sets the verbose flag.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.MeekRules
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.PcCommon
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyScoreBased
Sets the verbose mode for this FciOrientDataExaminationStrategyScoreBased object.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Sets the verbose mode for the FciOrientDataExaminationStrategy object.
setVerbose(boolean) - Method in interface edu.cmu.tetrad.search.utils.SepsetProducer
Sets the verbose mode of the SepsetProducer.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.SepsetsGreedy
Sets the verbosity level for this object.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.SepsetsMaxP
Sets the verbosity level for this object.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.SepsetsMinP
Sets the verbosity level for this object.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.SepsetsPossibleMsep
Sets the verbose mode of the SepsetProducer.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.SepsetsSet
Sets the verbose mode of the SepsetProducer.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.utils.TsDagToPag
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.FasFdr
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.GraspTol
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IGFci
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Sets the verbose flag to determine if verbose output should be enabled or disabled.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Sets the verbose flag.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
Sets whether this test will print verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
Sets whether this test will print verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMnlrLr
Sets whether this test will print verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
Sets whether this test will print verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Sets the verbose mode to either enabled or disabled.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
Sets the verbose flag.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.ISFges
Sets the verbosity level for the application.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.Kpc
Sets whether verbose output should be printed.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.ProbabilisticMapIndependence
Sets whether this test will print verbose output.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpc
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.SampleVcpcFast
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.VcFas
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPc
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.simulation.GdistanceRandom
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.simulation.HsimAutoC
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.simulation.HsimAutoRun
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.simulation.HsimRepeatAC
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.cmu.tetrad.simulation.HsimRepeatAutoRun
Setter for the field verbose.
setVerbose(boolean) - Method in class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
Sets the verbose mode of the program.
setVerbose(boolean) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.PagSamplingRfci
Set the verbose flag.
setVerbose(boolean) - Method in class edu.pitt.dbmi.algo.bayesian.constraint.search.RfciBsc
Sets whether verbose output should be produced.
setWeight(int) - Method in class edu.cmu.tetrad.search.FciOrientDijkstra.DijkstraEdge
Sets the weight of the edge.
setWeight(String, double) - Method in class edu.cmu.tetrad.algcomparison.statistic.Statistics
Sets the utility weight of the statistic by the given name.
setWInit(Matrix) - Method in class edu.cmu.tetrad.search.FastIca
Sets the initial un-mixing matrix of dimension (n.comp, n.comp).
setWithoutReplacements(boolean) - Method in class edu.cmu.tetrad.data.BootstrapSampler
This method takes a dataset and a sample size and creates a new dataset containing that number of samples by drawing with replacement from the original dataset.
setWrite(boolean) - Method in class edu.cmu.tetrad.simulation.HsimAutoC
Setter for the field write.
setWrite(boolean) - Method in class edu.cmu.tetrad.simulation.HsimAutoRun
Setter for the field write.
setWrite(boolean) - Method in class edu.cmu.tetrad.simulation.HsimRepeatAC
Setter for the field write.
setWrite(boolean) - Method in class edu.cmu.tetrad.simulation.HsimRepeatAutoRun
Setter for the field write.
setWThreshold(double) - Method in class edu.cmu.tetrad.search.Dagma
Sets the value of the wThreshold field.
setWThreshold(double) - Method in class edu.cmu.tetrad.search.IcaLingD
Sets the threshold value for the W matrix.
severe(String) - Method in class edu.cmu.tetrad.util.LogUtils
severe.
Sextad - Class in edu.cmu.tetrad.search.utils
Represents an ordered sextad of nodes.
Sextad - Class in edu.cmu.tetrad.search.work_in_progress
Represents an ordered sextad of variables.
Sextad(int, int, int, int, int, int) - Constructor for class edu.cmu.tetrad.search.utils.Sextad
Constructor.
Sextad(Node[]) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Sextad
Constructor for Sextad.
Sextad(Node, Node, Node, Node, Node, Node) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Sextad
Constructor for Sextad.
SHD - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
The structural Hamming distance.
SHD - Enum constant in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Constant SHD
ShiftSearch - Class in edu.cmu.tetrad.search.utils
Tries to find a good shifting of variables to minimize average BIC for time-series data.
ShiftSearch(List<DataModel>) - Constructor for class edu.cmu.tetrad.search.utils.ShiftSearch
Constructor for ShiftSearch.
ShortDataBox - Class in edu.cmu.tetrad.data
Stores a 2D array of short data.
ShortDataBox(int, int) - Constructor for class edu.cmu.tetrad.data.ShortDataBox
Constructs an 2D short array consisting entirely of missing values (-99).
ShortDataBox(short[][]) - Constructor for class edu.cmu.tetrad.data.ShortDataBox
Constructs a new data box using the given 2D short data array as data.
shuffle(List<?>) - Static method in class edu.cmu.tetrad.util.RandomUtil
This is just the RandomUtil.shuffle method (thanks!) but using the Tetrad RandomUtil to get random numbers.
shuffleColumns(DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
shuffleColumns.
shuffleColumns2(List<DataSet>) - Static method in class edu.cmu.tetrad.data.DataTransforms
shuffleColumns2.
Significance - Enum constant in enum class edu.cmu.tetrad.search.utils.ClusterSignificance.CheckType
Check the significance using a regression model.
SIGNIFICANCE_CHECKED - Static variable in class edu.cmu.tetrad.util.Params
Constant SIGNIFICANCE_CHECKED="significanceChecked"
significant(List<Integer>, double) - Method in class edu.cmu.tetrad.search.utils.ClusterSignificance
Returns the p-value for the given cluster.
SimpleDataLoader - Class in edu.cmu.tetrad.data
SimpleDataLoader class.
SimpleRandomizer - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Randomizes a graph using existing factors by first removing all edges and then adding for each factor (a) an edge from the same factor at time lag 1 and (b) a given number of factors chosen uniformly from all lagged factors with lag > 0.
SimpleRandomizer(int, int, int, double) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.SimpleRandomizer
Constructor for SimpleRandomizer.
SIMPLIFIED_BPC - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcAlgorithmType
Even slower.
SIMPLIFIED_BPC_DEPTH_0 - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcAlgorithmType
This will work and does a good job for small models, no more than 4 latents.
SIMPLIFIED_BPC_DEPTH_1 - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcAlgorithmType
This is very slow.
simulate(GeneHistory) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator
Simulates (optionally) neither, either, or both of two three-dimensionaly data sets, rawData and measuredData.
simulate(GeneHistory) - Method in class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams
simulate.
simulateData(int, boolean) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Simulates a data set with the specified number of rows.
simulateData(int, boolean) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Simulates a data set with the specified number of rows.
simulateData(int, boolean) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Simulates a data set.
simulateData(int, boolean) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Simulates a data set with the specified number of rows.
simulateData(int, boolean) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Simulates a data set with the specified number of rows.
simulateData(int, boolean) - Method in interface edu.cmu.tetrad.data.Simulator
Simulates data from the model associated with this object.
simulateData(int, boolean) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Simulates data based on the given parameters.
simulateData(int, boolean) - Method in class edu.cmu.tetrad.sem.SemIm
Simulates data from the model associated with this object.
simulateData(int, boolean) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
Simulates data from the model associated with this object.
simulateData(int, boolean, int[]) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Simulates a sample with the given sample size.
simulateData(DataSet, boolean) - Method in interface edu.cmu.tetrad.bayes.BayesIm
Simulates data based on the provided data set and saves the latent data if specified.
simulateData(DataSet, boolean) - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Simulates data based on the provided data set and saves the latent data if specified.
simulateData(DataSet, boolean) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Simulates data for the given data set.
simulateData(DataSet, boolean) - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Simulates data based on the provided data set and saves the latent data if specified.
simulateData(DataSet, boolean) - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Simulates data based on the provided data set and saves the latent data if specified.
simulateData(DataSet, boolean, int[]) - Method in class edu.cmu.tetrad.bayes.MlBayesIm
simulateData.
simulateDataAvoidInfinity(int, boolean) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Simulates data avoiding infinity values.
simulateDataCholesky(int, boolean) - Method in class edu.cmu.tetrad.sem.SemIm
Simulates data from this Sem using a Cholesky decomposition of the implied covariance matrix.
simulateDataFisher(double[][], int, double) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Simulates data using the model of R.
simulateDataFisher(int) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Simulates data using the model of R.
simulateDataFisher(int) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Simulates data using the model of R.
simulateDataFisher(int, int, double) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Simulates data using the model of R.
simulateDataFisher(int, int, int, double, boolean) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
simulateDataFisher.
simulateDataMinimizeSurface(int, boolean) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Simulates data by minimizing the surface defined by the given sample size and whether latent data is saved.
simulateDataNSteps(int, boolean) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Simulates data for a given number of steps.
simulateDataRecursive(int) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
This simulates data by picking random values for the exogenous terms and percolating this information down through the SEM, assuming it is acyclic.
simulateDataRecursive(int, boolean) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
This simulates data by picking random values for the exogenous terms and percolating this information down through the SEM, assuming it is acyclic.
simulateDataRecursive(int, boolean) - Method in class edu.cmu.tetrad.sem.SemIm
simulateDataRecursive.
simulateDataReducedForm(int) - Method in class edu.cmu.tetrad.sem.LargeScaleSimulation
Simulates data using the model X = (I - B)Y^-1 * e.
simulateDataReducedForm(int, boolean) - Method in class edu.cmu.tetrad.sem.SemIm
simulateDataReducedForm.
simulateDataReducedForm(int, boolean) - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
simulateDataReducedForm.
SimulateNetwork - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
SimulateNetwork class.
SimulateNetworkMain - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin
SimulateNetworkMain class.
SimulateNetworkMain() - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.SimulateNetworkMain
Constructor for SimulateNetworkMain.
simulateOneRecord(Vector) - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
simulateOneRecord.
simulateOneRecord(Vector) - Method in class edu.cmu.tetrad.sem.SemIm
simulateOneRecord.
Simulation - Interface in edu.cmu.tetrad.algcomparison.simulation
The interface that simulations must implement.
SIMULATION_ERROR_TYPE - Static variable in class edu.cmu.tetrad.util.Params
Constant SIMULATION_ERROR_TYPE="simulationErrorType"
SIMULATION_PARAM1 - Static variable in class edu.cmu.tetrad.util.Params
Constant SIMULATION_PARAM1="simulationParam1"
SIMULATION_PARAM2 - Static variable in class edu.cmu.tetrad.util.Params
Constant SIMULATION_PARAM2="simulationParam2"
SimulationPath - Interface in edu.cmu.tetrad.algcomparison.statistic.utils
Some simulations may wish to implement this interface to specify a simulation path, which will be printed in the output.
Simulations - Class in edu.cmu.tetrad.algcomparison.simulation
A list of simulations to be compared.
Simulations() - Constructor for class edu.cmu.tetrad.algcomparison.simulation.Simulations
Constructor for Simulations.
SimulationTypes - Class in edu.cmu.tetrad.algcomparison.simulation
Jun 4, 2019 3:10:49 PM
SimulationUtils - Class in edu.cmu.tetrad.algcomparison.simulation
Jun 4, 2019 5:21:45 PM
Simulator - Interface in edu.cmu.tetrad.data
Created by jdramsey on 12/22/15.
SingleDatasetSimulation - Class in edu.cmu.tetrad.algcomparison.simulation
A Simulation implementation that returns a single supplied data set.
SingleDatasetSimulation(DataSet) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.SingleDatasetSimulation
A Simulation implementation that returns a single supplied data set.
SingleGraph - Class in edu.cmu.tetrad.algcomparison.graph
Stores a single graph for use in simulations, etc.
SingleGraph(Graph) - Constructor for class edu.cmu.tetrad.algcomparison.graph.SingleGraph
Constructor for SingleGraph.
SingleGraphAlg - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
PC.
SingleGraphAlg(Graph) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.SingleGraphAlg
Constructor for SingleGraphAlg.
SingleValue - Class in edu.cmu.tetrad.util.dist
A pretend distribution that always returns the given value when nextRandom() is called.
SingleValue(double) - Constructor for class edu.cmu.tetrad.util.dist.SingleValue
Constructs single value "distribution" using the given value.
size() - Method in class edu.cmu.tetrad.algcomparison.statistic.Statistics
The number of statistics.
size() - Method in interface edu.cmu.tetrad.data.Covariances
Returns the dimensiom of the matrix.
size() - Method in class edu.cmu.tetrad.data.CovariancesDoubleForkJoin
size.
size() - Method in class edu.cmu.tetrad.data.DataModelList
size() - Method in class edu.cmu.tetrad.data.IndependenceFacts
size.
size() - Method in class edu.cmu.tetrad.search.utils.SepsetMap
Returns the number of {x, y} in the key set of the map.
size() - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
size.
size() - Method in class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
size.
size() - Method in class edu.cmu.tetrad.util.Vector
size.
skeletonToMatrix(Graph) - Static method in class edu.pitt.csb.mgm.MixedUtils
skeletonToMatrix.
skew - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Score
The skew.
skew(double[], double[], boolean) - Static method in class edu.cmu.tetrad.search.FaskOrig
Calculates a left-right judgument using the skewness of two arrays of double values.
Skew - Class in edu.cmu.tetrad.algcomparison.algorithm.pairwise
Skew.
Skew - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The Skew rule.
Skew() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Skew
Constructor for Skew.
Skew(Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Skew
Constructor for Skew.
SKEW - Enum constant in enum class edu.cmu.tetrad.search.Fask.LeftRight
The skew rule from the Hyvarinen and Smith paper.
SKEW - Enum constant in enum class edu.cmu.tetrad.search.FaskOrig.LeftRight
The skew rule from the Hyvarinen and Smith paper.
SKEW_EDGE_THRESHOLD - Static variable in class edu.cmu.tetrad.util.Params
Constant SKEW_EDGE_THRESHOLD="skewEdgeThreshold"
SkewE - Class in edu.cmu.tetrad.algcomparison.algorithm.pairwise
SkewE.
SkewE - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The SkewE rule.
SkewE() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.SkewE
Constructor for SkewE.
SkewE(Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.SkewE
Constructor for SkewE.
skewness(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
skewness.
skewness(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
skewness.
skewness(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
skewness.
skewness(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
skewness.
SKIP_NUM_RECORDS - Static variable in class edu.cmu.tetrad.util.Params
Constant SKIP_NUM_RECORDS="skipNumRecords"
smooth(DoubleMatrix1D, DoubleMatrix1D) - Method in class edu.pitt.csb.mgm.ConvexProximal
Calculate value of g(X) and gradient of g(X) at the same time for efficiency reasons.
smooth(DoubleMatrix1D, DoubleMatrix1D) - Method in class edu.pitt.csb.mgm.Mgm
Smooth method calculates the smooth loss and gradient given input parameters.
smoothGradient(DoubleMatrix1D) - Method in class edu.pitt.csb.mgm.Mgm
Calculates the smooth gradient for a given input vector.
smoothValue(DoubleMatrix1D) - Method in class edu.pitt.csb.mgm.Mgm
Calculate the smooth value of the given input vector.
solve(Matrix, Matrix) - Static method in class edu.cmu.tetrad.util.TetradAlgebra
solve.
sortEdges(List<Edge>) - Static method in class edu.cmu.tetrad.graph.Edges
sortEdges.
Sp - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
SP (Sparsest Permutation)
Sp - Class in edu.cmu.tetrad.search
Implements the SP (Sparsest Permutation) algorithm.
Sp() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Sp
Constructor for Sp.
Sp(ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Sp
Constructor for Sp.
Sp(Score) - Constructor for class edu.cmu.tetrad.search.Sp
This algorithm will work with an arbitrary score.
SP - Enum constant in enum class edu.cmu.tetrad.search.LvLite.START_WITH
Start with SP.
SPACE - Enum constant in enum class edu.cmu.tetrad.util.TextTable.Delimiter
Constant SPACE
sparseMatrix(int, int) - Static method in class edu.cmu.tetrad.util.Matrix
sparseMatrix.
specialConfiguration(IndependenceTest, Knowledge, boolean) - Static method in class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased
Provides a special configuration for creating an instance of FciOrientDataExaminationStrategy.
specialConfiguration(TeyssierScorer, Knowledge, boolean, int) - Static method in class edu.cmu.tetrad.search.utils.R0R4StrategyScoreBased
Returns a special configuration of FciOrientDataExaminationStrategy.
SpFci - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
Adjusts GFCI to use a permutation algorithm (in this case SP) to do the initial steps of finding adjacencies and unshielded colliders.
SpFci - Class in edu.cmu.tetrad.search
Uses SP in place of FGES for the initial step in the GFCI algorithm.
SpFci() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
The SpFci class represents a specific algorithm for structural learning called "Conditional Independence Test-based Fast Causal Inference" (SpFci).
SpFci(IndependenceWrapper, ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci
Constructor for the SpFci class.
SpFci(IndependenceTest, Score) - Constructor for class edu.cmu.tetrad.search.SpFci
Constructor; requires by ta test and a score, over the same variables.
split(DataSet, double) - Static method in class edu.cmu.tetrad.data.DataTransforms
split.
Split - Class in edu.cmu.tetrad.util.dist
Wraps a chi square distribution for purposes of drawing random samples.
Split(double, double) - Constructor for class edu.cmu.tetrad.util.dist.Split
Creates a new split distribution, drawing uniformly from [-b, -a] U [a, b], where a and b are positive real numbers.
SplitCasesSpec - Class in edu.cmu.tetrad.data
Specifies how a column (continuous or discrete) should be discretized.
SplitCasesSpec(int, int[], List<String>) - Constructor for class edu.cmu.tetrad.data.SplitCasesSpec
Constructor for SplitCasesSpec.
sqrt() - Method in class edu.cmu.tetrad.util.Matrix
sqrt.
SQUARED - Enum constant in enum class edu.cmu.tetrad.search.CpdagParentDistancesFromTrue.DistanceType
Calculate the squared distance between the true edge strength and the range of estimated coefficients.
SquaredErrorLoss - Class in edu.cmu.tetrad.cluster.metrics
Euclidean dissimilarity metric--i.e., the sum of the differences in corresponding variable values.
SquaredErrorLoss() - Constructor for class edu.cmu.tetrad.cluster.metrics.SquaredErrorLoss
Calculates the squared error dissimilarity between two vectors using the Euclidean dissimilarity metric.
squareLayout(Graph) - Static method in class edu.cmu.tetrad.graph.LayoutUtil
squareLayout.
sSquare(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
sSquare.
sSquare(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
sSquare.
sSquare(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
sSquare.
sSquare(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
sSquare.
ssx(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
ssx.
ssx(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
ssx.
ssx(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
ssx.
ssx(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
ssx.
StabilitySearch(DataSet, DataGraphSearch, int, int) - Static method in class edu.pitt.csb.stability.StabilityUtils
StabilitySearch.
StabilitySearchPar(DataSet, DataGraphSearch, int, int) - Static method in class edu.pitt.csb.stability.StabilityUtils
StabilitySearchPar.
StabilitySelection - Class in edu.cmu.tetrad.algcomparison.algorithm
Stability selection.
StabilitySelection(Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection
Constructor for StabilitySelection.
StabilityUtils - Class in edu.pitt.csb.stability
Runs a search algorithm over a N subsamples of size b to asses stability as in "Stability Selection" and "Stability Approach to Regularization Selection"
STABLE - Enum constant in enum class edu.cmu.tetrad.search.utils.PcCommon.FasType
Stable FAS.
STABLE_FAS - Static variable in class edu.cmu.tetrad.util.Params
Constant STABLE_FAS="stableFAS"
stampWithBic(Graph, DataModel) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
stampWithBic.
stampWithScore(Graph, Score) - Static method in class edu.cmu.tetrad.search.utils.LogUtilsSearch
stampWithScore.
STANDARDIZE - Static variable in class edu.cmu.tetrad.util.Params
Constant STANDARDIZE="standardize"
STANDARDIZED_STRUCTURAL_EQUATION_MODEL - Static variable in class edu.cmu.tetrad.algcomparison.simulation.SimulationTypes
Constant STANDARDIZED_STRUCTURAL_EQUATION_MODEL="Standardized Structural Equation Model"
standardizeData(double[]) - Static method in class edu.cmu.tetrad.data.DataTransforms
standardizeData.
standardizeData(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
standardizeData.
standardizeData(DoubleArrayList) - Static method in class edu.cmu.tetrad.data.DataTransforms
standardizeData.
standardizeData(DataSet) - Static method in class edu.cmu.tetrad.data.DataTransforms
standardizeData.
standardizeData(Matrix) - Static method in class edu.cmu.tetrad.data.DataTransforms
standardizeData.
standardizeData(Matrix, List<Node>) - Static method in class edu.cmu.tetrad.data.DataTransforms
 
standardizeData(List<DataSet>) - Static method in class edu.cmu.tetrad.data.DataTransforms
standardizeData.
standardizeData(SimpleMatrix) - Static method in class edu.cmu.tetrad.search.test.Kci
 
standardizedFifthMoment(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
standardizedFifthMoment.
standardizedFifthMoment(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
standardizedFifthMoment.
StandardizedSemIm - Class in edu.cmu.tetrad.sem
A special SEM model in which variances of variables are always 1 and means of variables are always 0.
StandardizedSemIm(SemIm, StandardizedSemIm.Initialization, Parameters) - Constructor for class edu.cmu.tetrad.sem.StandardizedSemIm
Constructs a new standardized SEM IM from the freeParameters in the given SEM IM.
StandardizedSemIm(SemIm, Parameters) - Constructor for class edu.cmu.tetrad.sem.StandardizedSemIm
Constructs a new standardized SEM IM, initializing from the freeParameters in the given SEM IM.
StandardizedSemIm.Initialization - Enum Class in edu.cmu.tetrad.sem
The initialization method for the model.
StandardizedSemIm.ParameterRange - Class in edu.cmu.tetrad.sem
Stores a coefficient range--i.e.
StandardizedSemSimulation - Class in edu.cmu.tetrad.algcomparison.simulation
Standardized SEM simulation.
StandardizedSemSimulation(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
Constructor for StandardizedSemSimulation.
StandardizedSemSimulation(SemPm) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
Constructor for StandardizedSemSimulation.
StandardizedSemSimulation(StandardizedSemIm) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation
Constructor for StandardizedSemSimulation.
standardizedSixthMoment(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
standardizedSixthMoment.
standardizedSixthMoment(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
standardizedSixthMoment.
STAR - Enum constant in enum class edu.cmu.tetrad.graph.Endpoint
Star endpoint.
StARS - Class in edu.cmu.tetrad.algcomparison.algorithm
StARS
StARS(Algorithm, String, double, double) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.StARS
Constructor for StARS.
startsWithPrefixes() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
startsWithPrefixes.
Statistic - Interface in edu.cmu.tetrad.algcomparison.statistic
The interface that each statistic needs to implement.
Statistics - Class in edu.cmu.tetrad.algcomparison.statistic
A list of statistics and their utility weights.
Statistics() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.Statistics
Constructor for Statistics.
StatUtils - Class in edu.cmu.tetrad.util
Contains a number of basic statistical functions.
stop() - Method in class edu.cmu.tetrad.search.utils.ShiftSearch
stop.
StoredCellProbs - Class in edu.cmu.tetrad.bayes
Creates a table of stored cell probabilities for the given list of variables.
StoredCellProbsObs - Class in edu.cmu.tetrad.bayes
Creates a table of stored cell probabilities for the given list of variables.
StoredCellProbsObs(List<Node>) - Constructor for class edu.cmu.tetrad.bayes.StoredCellProbsObs
Constructor for StoredCellProbsObs.
StoredLagGraphParams - Class in edu.cmu.tetrad.study.gene.tetrad.gene.graph
Stores a file for reading in a lag graph from a file.
StoredLagGraphParams() - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.graph.StoredLagGraphParams
Constructs a new parameters object.
stouffer - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Stouffer et al.'s method
stouffer - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
The stouffer method.
STRING - Enum constant in enum class edu.cmu.tetrad.calculator.parser.Token
String.
stringFrom2dArray(int[][]) - Static method in class edu.pitt.csb.mgm.MixedUtils
stringFrom2dArray.
strOfParents(int) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.BiolinguaDigraph
Returns a string with the indexes of all parents of node i separated by spaces (useful for printouts)
STRUCTURAL_EQUATION_MODEL - Static variable in class edu.cmu.tetrad.algcomparison.simulation.SimulationTypes
Constant STRUCTURAL_EQUATION_MODEL="Linear Structural Equation Model"
structuralHammingDistance(Graph, Graph) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
Tsamardinos, I., Brown, L.
StructuralHammingDistance - Class in edu.cmu.tetrad.algcomparison.statistic
Calculates the structural Hamming distance (SHD) between the estimated graph and the true graph.
StructuralHammingDistance() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.StructuralHammingDistance
Constructs the statistic.
structuralVar(DataSet, int) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
structuralVar.
STRUCTURE_PRIOR - Static variable in class edu.cmu.tetrad.util.Params
Constant STRUCTURE_PRIOR="structurePrior"
subgraph(List<Node>) - Method in class edu.cmu.tetrad.graph.Dag
Returns a subgraph of the current graph consisting only of the specified nodes.
subgraph(List<Node>) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Constructs and returns a subgraph consisting of a given subset of the nodes of this graph together with the edges between them.
subgraph(List<Node>) - Method in interface edu.cmu.tetrad.graph.Graph
Constructs and returns a subgraph consisting of a given subset of the nodes of this graph together with the edges between them.
subgraph(List<Node>) - Method in class edu.cmu.tetrad.graph.LagGraph
Constructs and returns a subgraph consisting of a given subset of the nodes of this graph together with the edges between them.
subgraph(List<Node>) - Method in class edu.cmu.tetrad.graph.SemGraph
Constructs and returns a subgraph consisting of a given subset of the nodes of this graph together with the edges between them.
subgraph(List<Node>) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Returns a subgraph of the current graph based on the provided nodes.
SublistGenerator - Class in edu.cmu.tetrad.util
Generates (nonrecursively) all of the sublists of size b from a list of size a, where a, b are nonnegative integers and a >= b.
SublistGenerator(int, int) - Constructor for class edu.cmu.tetrad.util.SublistGenerator
Constructs a new generator for sublists for a list of size b taken a at a time.
submatrix(double[][], int) - Static method in class edu.cmu.tetrad.util.MatrixUtils
A copy of the original (square) matrix with the stated index row/column removed
subMatrix(ICovarianceMatrix, Node, Node, List<Node>) - Static method in class edu.cmu.tetrad.data.DataUtils
subMatrix.
subMatrix(ICovarianceMatrix, Map<Node, Integer>, Node, Node, List<Node>) - Static method in class edu.cmu.tetrad.data.DataUtils
subMatrix.
subMatrix(Matrix, List<Node>, Node, Node, List<Node>) - Static method in class edu.cmu.tetrad.data.DataUtils
subMatrix.
subMatrix(Matrix, Map<Node, Integer>, Node, Node, List<Node>) - Static method in class edu.cmu.tetrad.data.DataUtils
subMatrix.
SuborderSearch - Interface in edu.cmu.tetrad.search
An interface for suborder searches for various types of permutation algorithms.
SUBSAMPLE - Enum constant in enum class edu.cmu.tetrad.search.Cstar.SampleStyle
Use subsample.
subSampleNoReplacement(int, int, int) - Static method in class edu.pitt.csb.stability.StabilityUtils
subSampleNoReplacement.
subset(List<Node>) - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns a SEM BIC score for the given subset of variables.
subsetColumns(int[]) - Method in class edu.cmu.tetrad.data.BoxDataSet
Creates a new DataSet object containing only the specified columns.
subsetColumns(int[]) - Method in interface edu.cmu.tetrad.data.DataSet
subsetColumns.
subsetColumns(int[]) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
subsetColumns.
subsetColumns(List<Node>) - Method in class edu.cmu.tetrad.data.BoxDataSet
Creates and returns a dataset consisting of those variables in the list vars.
subsetColumns(List<Node>) - Method in interface edu.cmu.tetrad.data.DataSet
Creates and returns a dataset consisting of those variables in the list vars.
subsetColumns(List<Node>) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Creates and returns a dataset consisting of those variables in the list vars.
subsetRows(int[]) - Method in class edu.cmu.tetrad.data.BoxDataSet
Creates a subset of rows from the existing DataSet.
subsetRows(int[]) - Method in interface edu.cmu.tetrad.data.DataSet
subsetRows.
subsetRows(int[]) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
subsetRows.
subsetRowsColumns(int[], int[]) - Method in class edu.cmu.tetrad.data.BoxDataSet
Generates a subset of the current DataSet by selecting specified rows and columns.
subsetRowsColumns(int[], int[]) - Method in interface edu.cmu.tetrad.data.DataSet
Generates a subset of the current DataSet by selecting specified rows and columns.
subsetRowsColumns(int[], int[]) - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
Generates a subset of the current DataSet by selecting specified rows and columns.
subtract(double[][], double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
subtract.
subtract(double[], double[]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
subtract.
successiveFactorVarimax(Matrix) - Method in class edu.cmu.tetrad.search.FactorAnalysis
Returns the matrix result for the varimax algorithm.
successiveResidual() - Method in class edu.cmu.tetrad.search.FactorAnalysis
Successive method with residual matrix.
suite() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.TestRevealEvaluator
This method uses reflection to collect up all of the test methods from this class and return them to the test runner.
suite() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestBooleanFunction
This method uses reflection to collect up all of the test methods from this class and return them to the test runner.
suite() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestIndexedConnectivity
This method uses reflection to collect up all of the test methods from this class and return them to the test runner.
suite() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestIndexedLagGraph
This method uses reflection to collect up all of the test methods from this class and return them to the test runner.
suite() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestPolynomial
This method uses reflection to collect up all of the test methods from this class and return them to the test runner.
suite() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestPolynomialTerm
This method uses reflection to collect up all of the test methods from this class and return them to the test runner.
suite() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestSimpleRandomizer
This method uses reflection to collect up all of the test methods from this class and return them to the test runner.
suite() - Static method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.TestMeasurementSimulator
This method uses reflection to collect up all of the test methods from this class and return them to the test runner.
sum(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
sum.
sum(double[][], double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
sum.
sum(double[], double[]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
sum.
sum(int) - Method in class edu.cmu.tetrad.util.Matrix
sum.
sum0ToN(int) - Static method in class edu.cmu.tetrad.util.MatrixUtils
sum0ToN.
sumBits(byte[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.akutsu.BoolSearch
Returns the sum of the bits in the byte array b.
sumBits(byte[]) - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.BoolSearch
sumBits.
summarize(List<ComparisonResult>, List<Comparison.TableColumn>) - Static method in class edu.cmu.tetrad.study.performance.Comparison
summarize.
summarize(List<ComparisonResult>, List<Comparison2.TableColumn>) - Static method in class edu.cmu.tetrad.study.performance.Comparison2
summarize.
sumOfArCoefficients(DataSet, int) - Static method in class edu.cmu.tetrad.search.utils.TsUtils
sumOfArCoefficients.
SvarFas - Class in edu.cmu.tetrad.search
Adapts FAS for the time series setting, assuming the data is generated by a SVAR (structural vector autoregression).
SvarFas(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.SvarFas
Constructs a new FastAdjacencySearch.
SvarFci - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
The SvarFci class is an implementation of the SVAR Fast Causal Inference algorithm.
SvarFci - Class in edu.cmu.tetrad.search
Adapts FCI for the time series setting, assuming the data is generated by a SVAR (structural vector autoregression).
SvarFci() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarFci
Represents a constructor for the SvarFci class.
SvarFci(IndependenceWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarFci
Represents a constructor for the SvarFci class.
SvarFci(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.SvarFci
Constructs a new FCI search for the given independence test and background knowledge.
SVARFCI - Enum constant in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.Algorithm
Constant for the SVARFCI algorithm.
SvarFges - Class in edu.cmu.tetrad.search
Adapts FGES for the time series setting, assuming the data is generated by a SVAR (structural vector autoregression).
SvarFges(Score) - Constructor for class edu.cmu.tetrad.search.SvarFges
Construct a Score and pass it in here.
SvarGfci - Class in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
SvarGfci class is an implementation of the SVAR GFCI algorithm.
SvarGfci - Class in edu.cmu.tetrad.search
Represents a GFCI search algorithm for structure learning in causal discovery.
SvarGfci() - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Constructor for SvarGfci.
SvarGfci(IndependenceWrapper, ScoreWrapper) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SvarGfci
Constructor for SvarGfci.
SvarGfci(IndependenceTest, Score) - Constructor for class edu.cmu.tetrad.search.SvarGfci
Constructs a new GFCI search for the given independence test and background knowledge.
SvarSetEndpointStrategy - Class in edu.cmu.tetrad.search.utils
The SvarSetEndpointStrategy class implements the SetEndpointStrategy interface and provides a strategy for setting the endpoint of an edge in a graph.
SvarSetEndpointStrategy(IndependenceTest, Knowledge) - Constructor for class edu.cmu.tetrad.search.utils.SvarSetEndpointStrategy
Creates a new instance of SvarSetEndpointStrategy with the given IndependenceTest and Knowledge.
swap(Node, Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Swaps m and n in the permutation.
SWAP - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move.Type
Swap two edges.
sxy(double[], double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
sxy.
sxy(double[], double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
sxy.
sxy(long[], long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
sxy.
sxy(long[], long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
sxy.
sxy(Vector, Vector, int) - Static method in class edu.cmu.tetrad.util.StatUtils
sxy.
SymMatrix - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util
Implements a space-efficient symmetric matrix (of elements of type short), storing only the lower triangular portion of it
SymMatrix(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrix
Creates a symmetric matrix reading it from file fname.
SymMatrix(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrix
Creates a symmetric matrix with nrows rows.
SymMatrixF - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util
Implements a space-efficient symmetric matrix (of elements of type short), storing only the lower triangular portion of it
SymMatrixF(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrixF
Creates a symmetric matrix reading it from file fname.
SymMatrixF(String, int) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrixF
Creates a symmetric matrix with nrows rows.
SYMMETRIC_FIRST_STEP - Static variable in class edu.cmu.tetrad.util.Params
Constant SYMMETRIC_FIRST_STEP="symmetricFirstStep"
symmetricDirichletIm(BayesPm, double) - Static method in class edu.cmu.tetrad.bayes.DirichletBayesIm
symmetricDirichletIm.
symmetry() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Checks is symmetry holds--i.e., X ⊥⊥ Y | Z ==> Y ⊥⊥ X | Z

T

ta - Enum constant in enum class edu.cmu.tetrad.graph.EdgeTypeProbability.EdgeType
Tail-to-arrow
TAB - Enum constant in enum class edu.cmu.tetrad.util.TextTable.Delimiter
Constant TAB
TAB - Static variable in class edu.cmu.tetrad.data.DelimiterType
Constant TAB
TAIL - Enum constant in enum class edu.cmu.tetrad.graph.Endpoint
Tail endpoint.
TailConfusion - Class in edu.cmu.tetrad.algcomparison.statistic.utils
A confusion matrix for tails--i.e.
TailConfusion(Graph, Graph) - Constructor for class edu.cmu.tetrad.algcomparison.statistic.utils.TailConfusion
Constructor for TailConfusion.
TailPrecision - Class in edu.cmu.tetrad.algcomparison.statistic
TailPrecision is a class that implements the Statistic interface.
TailPrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TailPrecision
Constructs the statistic.
TailRecall - Class in edu.cmu.tetrad.algcomparison.statistic
Implements the TailRecall statistic, which calculates the tail recall value for a given true graph, estimated graph, and data model.
TailRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TailRecall
Constructs the statistic.
TakesCovarianceMatrix - Interface in edu.cmu.tetrad.algcomparison.algorithm
Tags algorithm comparison wrappers that can take a covariance matrix as input.
TakesData - Interface in edu.cmu.tetrad.algcomparison.utils
Tags a gadget that takes a data model list as argument to its constructor.
takesExternalGraph(Class) - Method in class edu.cmu.tetrad.annotation.AlgorithmAnnotations
Checks if the algorithm takes an external graph.
TakesExternalGraph - Interface in edu.cmu.tetrad.algcomparison.utils
Tags an algorithm that can take an external graph as input.
TakesGraph - Interface in edu.cmu.tetrad.algcomparison.independence
TakesGraph interface.
TakesIndependenceWrapper - Interface in edu.cmu.tetrad.algcomparison.utils
Tags an algorithm as using an independence wrapper.
takesKnowledge(Class) - Method in class edu.cmu.tetrad.annotation.AlgorithmAnnotations
Checks if the algorithm takes knowledge.
takesMultipleDataset(Class) - Method in class edu.cmu.tetrad.annotation.AlgorithmAnnotations
Checks if the algorithm takes multiple data sets.
Tanh - Class in edu.cmu.tetrad.algcomparison.algorithm.pairwise
Tanh.
Tanh - Enum constant in enum class edu.cmu.tetrad.search.Lofs.Rule
The Tahn rule.
Tanh(Algorithm) - Constructor for class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Tanh
Constructor for Tanh.
TANH - Enum constant in enum class edu.cmu.tetrad.search.Fask.LeftRight
The tanh rule from the Hyvarinen and Smith paper.
TANH - Enum constant in enum class edu.cmu.tetrad.search.FaskOrig.LeftRight
The tanh rule from the Hyvarinen and Smith paper.
TARGET_NAME - Static variable in class edu.cmu.tetrad.util.Params
Constant TARGET_NAME="targetName"
TARGETS - Static variable in class edu.cmu.tetrad.util.Params
Constant TARGETS="targets"
TaskManager - Class in edu.cmu.tetrad.util
This cancels all processes that check the TaskManager.getInstance().isCanceled() method.
TaskRunner<T> - Class in edu.cmu.tetrad.util
This class is for running a list of tasks that implement Callable.
TaskRunner() - Constructor for class edu.cmu.tetrad.util.TaskRunner
This class is responsible for running a list of tasks that implement the Callable interface in parallel using multiple threads.
TaskRunner(int) - Constructor for class edu.cmu.tetrad.util.TaskRunner
Initializes a TaskRunner with the specified number of threads.
tautology(VariableSource) - Static method in class edu.cmu.tetrad.bayes.Evidence
tautology.
tautology(VariableSource) - Static method in class edu.cmu.tetrad.bayes.Proposition
tautology.
tautology(SemIm) - Static method in class edu.cmu.tetrad.sem.SemProposition
Creates a tautology by wrapping the given SemIm object.
tCdf(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
CACM Algorithm 395, by G.
tearDown() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestSimpleRandomizer
tearDown.
TemplateExpander - Class in edu.cmu.tetrad.sem
Expands templates for the generalized SEM PM.
TEST_TIMEOUT - Static variable in class edu.cmu.tetrad.util.Params
Constant TEST_TIMEOUT="testTimeout"
TestBooleanFunction - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Tests the BooleanFunction class.
TestBooleanFunction(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestBooleanFunction
Standard constructor for JUnit test cases.
TestBoss - Class in edu.cmu.tetrad.algcomparison.examples
Test the degenerate Gaussian score.
TestBoss() - Constructor for class edu.cmu.tetrad.algcomparison.examples.TestBoss
Initializes a new instance of the TestBoss class.
testChipToChipError() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.TestMeasurementSimulator
Turn on chip to chip error, turn off all other sources of error, simulate 1 dish of data with 1000 samples per dish and look to see whether in the aggregated data the standard deviations for Gene2:t1, Gene3:t1, and Gene1:t2 are 0.3.
testCompareDagToCPDAG(int) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testCompareDagToCPDAG.
testComparePcVersions(int, double, int) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testComparePcVersions.
testConstantIndegree() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestSimpleRandomizer
Tests whether the randomizer can randomly make a graph where all of the factors have the same indegree.
testConstruction() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestIndexedConnectivity
testConstruction.
testConstruction() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestIndexedLagGraph
testConstruction.
testConstruction() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestPolynomial
Tests to make sure that null parent throw an exception.
testConstruction() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestPolynomialTerm
Tests to make sure that null parent throw an exception.
testCpc(int, double, int) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testCpc.
testCpcStable(int, double, int, double) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testCpcStable.
testDefaultParameterSettings() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.TestMeasurementSimulator
Test to make sure the accessor methods are working correctly.
TestDegenerateGaussian - Class in edu.cmu.tetrad.algcomparison.examples
Test the degenerate Gaussian score.
TestDegenerateGaussian() - Constructor for class edu.cmu.tetrad.algcomparison.examples.TestDegenerateGaussian
Initializes a new instance of the TestDegenerateGaussian class.
testDishToDishVariability() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.TestMeasurementSimulator
Turn on dish-to-dish variability error, turn off all other sources of error, simulate 100 dishes of data with 1 sample per dish, and look to see whether in the aggregated data Gene2:t1 and Gene3:t1 have standard deviations that are 10% of their respective means.
testEvaluation() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestPolynomial
Test the evaluation of terms.
testEvaluation() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestPolynomialTerm
Test the evaluation of terms.
testFci(int, double, int) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testFci.
testFges(int, double, int, double) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testFges.
testFgesComparisonContinuous(int, double, int, int) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testFgesComparisonContinuous.
testFgesComparisonDiscrete(int, double, int, int) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testFgesComparisonDiscrete.
testFgesMbComparisonContinuous(int, double, int, int) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testFgesMbComparisonContinuous.
testFgesMbComparisonDiscrete(int, double, int, int) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testFgesMbComparisonDiscrete.
testGfci(int, double) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testGfci.
testGFciComparison() - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testGFciComparison.
testGigaflops() - Static method in class edu.cmu.tetrad.algcomparison.examples.TestBoss
testGigaflops.
TestIndexedConnectivity - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Tests the IndexedConnectivity class by constructing graphs with randomly chosen parameters and seeing if they have the required properties.
TestIndexedConnectivity(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestIndexedConnectivity
Change the name of this constructor to match the name of the test class.
TestIndexedLagGraph - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Tests the IndexedLagGraph class by constructing graphs with randomly chosen parameters and seeing if they have the required properties.
TestIndexedLagGraph(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestIndexedLagGraph
Change the name of this constructor to match the name of the test class.
testIsCanalyzing() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestBooleanFunction
Tests to see whether some known canalyzing functions (AND, OR, ...) pass the isCanalyzing() test.
testIsEffective() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestBooleanFunction
Tests to see whether some known effective functions pass the isEffective() test.
testLiangFigure6() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.TestRevealEvaluator
Tests whether the calculations in Liang, Figure 6 come out to the correct values.
testMain() - Method in class edu.pitt.dbmi.algo.bayesian.constraint.inference.BayesianConstraintInferenceTest
Test of main method, of class BayesianConstraintInference.
testMaxIndegree() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestSimpleRandomizer
Tests whether the randomizer can randomly make a graph where the maximum indegree across factors is the given factor.
testMeanIndegree() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestSimpleRandomizer
Tests whether the randomizer can randomly make a graph where the mean ofindegree across factors is the given number.
TestMeasurementSimulator - Class in edu.cmu.tetrad.study.gene.tetrad.gene.simulation
Tests the MeasurementSimulator class using diagnostics devised by Richard Scheines.
TestMeasurementSimulator(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.TestMeasurementSimulator
Standard constructor for JUnit test cases.
testNullConstruction() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestBooleanFunction
Tests to make sure that null parent throw an exception.
TestOfIndependence - Annotation Interface in edu.cmu.tetrad.annotation
Aug 31, 2017 4:42:08 PM
TestOfIndependenceAnnotations - Class in edu.cmu.tetrad.annotation
Sep 26, 2017 1:18:28 AM
testPc(int, double, int, double) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testPc.
testPcStable(int, double, int, double) - Method in class edu.cmu.tetrad.study.performance.PerformanceTests
testPcStable.
testPixelError() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.TestMeasurementSimulator
Turn on pixel digitalization error, turn off all other sources of error, simulate 1 dish of data with 1000 samples per dish and look to see whether in the aggregated data the standard deviations for Gene2:t1, Gene3:t1 and Gene1:t2 are 0.3.
TestPolynomial - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Tests the Polynomial class.
TestPolynomial(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestPolynomial
Standard constructor for JUnit test cases.
TestPolynomialTerm - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Tests the PolynomialTerm class.
TestPolynomialTerm(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestPolynomialTerm
Standard constructor for JUnit test cases.
testPrint(int) - Static method in class edu.cmu.tetrad.util.PermutationGenerator
This static method will print the series of combinations for numObjects choose b to System.out.
testPrint(int) - Static method in class edu.cmu.tetrad.util.SelectionGenerator
This static method will print the series of combinations for a choose b to System.out.
testPrint(int[]) - Static method in class edu.cmu.tetrad.util.CombinationGenerator
This static method will print the series of combinations for a choose b to System.out.
testPrint(int, int) - Static method in class edu.cmu.tetrad.util.ChoiceGenerator
This static method will print the series of combinations for a choose b to System.out.
testPrint(int, int) - Static method in class edu.cmu.tetrad.util.SublistGenerator
This static method will print the series of combinations for a choose depth to System.out.
TestRevealEvaluator - Class in edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal
Test the Reveal evaluator.
TestRevealEvaluator(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.reveal.TestRevealEvaluator
Standard constructor for JUnit test cases.
testRowOrder() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestBooleanFunction
Tests whether rows are stored in the correct order.
testSampleToSampleError() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.TestMeasurementSimulator
Turn on sample-to-sample error, turn off all other sources of error, simulate 1 dish of data with 1000 samples per dish, and look to see whether in the aggregated data the standard deviations of Gene2:t1 and Gene3:t1 are 0.2.
TestSimpleRandomizer - Class in edu.cmu.tetrad.study.gene.tetrad.gene.history
Tests the SimpleRandomizer class by constructing graphs with randomly chosen parameters and seeing if they have the required properties.
TestSimpleRandomizer(String) - Constructor for class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestSimpleRandomizer
Change the name of this constructor to match the name of the test class.
testTableSize() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.TestBooleanFunction
Tests to make sure the table is the correct size.
testTranscriptionError() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.TestMeasurementSimulator
Save out the raw data using default parameters and make sure that Gene1:t2 has the specified standard deviation.
Tetrad - Class in edu.cmu.tetrad.search.utils
Represents a ordered tetrad of variables, (i, j, k, l).
Tetrad(Node, Node, Node, Node) - Constructor for class edu.cmu.tetrad.search.utils.Tetrad
Constructor for Tetrad.
Tetrad(Node, Node, Node, Node, double) - Constructor for class edu.cmu.tetrad.search.utils.Tetrad
Constructor for Tetrad.
TETRAD_BASED - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
Tetrad-based test.
TETRAD_BOLLEN - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
Bollen Tetrad test.
TETRAD_DELTA - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
Delta Tetrad test.
TETRAD_PURIFY_WASHDOWN - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcAlgorithmType
This option doesn't do any purify.
TETRAD_WISHART - Enum constant in enum class edu.cmu.tetrad.search.utils.BpcTestType
Wishart Tetrad test.
TetradAlgebra - Class in edu.cmu.tetrad.util
Some algebra methods.
TetradAlgebra() - Constructor for class edu.cmu.tetrad.util.TetradAlgebra
Initializes a new instance of the TetradAlgebra class.
tetradHolds(int, int, int, int) - Method in interface edu.cmu.tetrad.search.utils.TetradTest
tetradHolds.
tetradHolds(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
tetradHolds.
tetradHolds(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
tetradHolds.
tetradHolds(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
tetradHolds.
TetradLogger - Class in edu.cmu.tetrad.util
Represents a logging utility used throughout tetrad.
TetradLogger.EmptyConfig - Class in edu.cmu.tetrad.util
Represents an empty configuration for the logger.
TetradLogger.LogDisplayOutputStream - Interface in edu.cmu.tetrad.util
Represents an output stream that can get its own length.
TetradLoggerConfig - Interface in edu.cmu.tetrad.util
Represents the configuration for the logger.
TetradLoggerConfig.Event - Interface in edu.cmu.tetrad.util
Represents an event which is just an id and a description.
TetradLoggerEvent - Class in edu.cmu.tetrad.util
An event associated with the TetradLoggerListener.
TetradLoggerEvent(Object, TetradLoggerConfig) - Constructor for class edu.cmu.tetrad.util.TetradLoggerEvent
Constructs the event given the source and the TetradLoggerConfig associated with the event if there is one
TetradLoggerListener - Interface in edu.cmu.tetrad.util
A listener for tetrad's logger.
TetradProperties - Class in edu.cmu.tetrad.util
Nov 10, 2017 4:14:31 PM
tetradPValue(int, int, int, int) - Method in interface edu.cmu.tetrad.search.utils.TetradTest
tetradPValue.
tetradPValue(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
tetradPValue.
tetradPValue(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
tetradPValue.
tetradPValue(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
tetradPValue.
tetradScore(int, int, int, int) - Method in interface edu.cmu.tetrad.search.utils.TetradTest
tetradScore.
tetradScore(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
tetradScore.
tetradScore(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
tetradScore.
tetradScore(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
tetradScore.
tetradScore1(int, int, int, int) - Method in interface edu.cmu.tetrad.search.utils.TetradTest
tetradScore1.
tetradScore1(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
tetradScore1.
tetradScore1(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
tetradScore1.
tetradScore1(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
tetradScore1.
tetradScore3(int, int, int, int) - Method in interface edu.cmu.tetrad.search.utils.TetradTest
tetradScore3.
tetradScore3(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
tetradScore3.
tetradScore3(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
tetradScore3.
tetradScore3(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
tetradScore3.
TetradSerializable - Interface in edu.cmu.tetrad.util
Interface to tag a class that is part of the set of serializable classes in the Tetrad API.
TetradSerializableExcluded - Interface in edu.cmu.tetrad.util
Interface to tag a class that should be exluded from the set of TetradSerializable classes, even if it implements the TetradSerializable interface.
TetradSerializableUtils - Class in edu.cmu.tetrad.util
Contains methods used by TestSerialization to ensure that previous "stable" versions of Tetrad will by loadable by later "stable" versions of Tetrad.
TetradSerializableUtils(String, String, String) - Constructor for class edu.cmu.tetrad.util.TetradSerializableUtils
Blank constructor.
TetradTest - Interface in edu.cmu.tetrad.search.utils
Provides an interface for classes that test tetrad constraints.
TetradTestContinuous - Class in edu.cmu.tetrad.search.utils
Implements different tests of tetrad constraints: using Wishart's test (CPS, Wishart 1928); Bollen's test (Bollen, 1990) or a more computationally intensive test that fits one/two factor Gaussian models.
TetradTestContinuous(CorrelationMatrix, BpcTestType, double) - Constructor for class edu.cmu.tetrad.search.utils.TetradTestContinuous
Constructor for TetradTestContinuous.
TetradTestContinuous(DataSet, BpcTestType, double) - Constructor for class edu.cmu.tetrad.search.utils.TetradTestContinuous
Constructor for TetradTestContinuous.
TetradTestContinuous(ICovarianceMatrix, BpcTestType, double) - Constructor for class edu.cmu.tetrad.search.utils.TetradTestContinuous
Constructor for TetradTestContinuous.
TetradTestDiscrete - Class in edu.cmu.tetrad.search.utils
Implements a test of tetrad constraints with discrete variables.
TetradTestDiscrete(DataSet, double) - Constructor for class edu.cmu.tetrad.search.utils.TetradTestDiscrete
Constructor for TetradTestDiscrete.
TetradTestPopulation - Class in edu.cmu.tetrad.search.utils
Implements a test of tetrad constraints in a known correlation matrix.
TetradTestPopulation(CorrelationMatrix) - Constructor for class edu.cmu.tetrad.search.utils.TetradTestPopulation
Constructor for TetradTestPopulation.
TextTable - Class in edu.cmu.tetrad.util
Stores a 2D array of Strings for printing out tables.
TextTable(int, int) - Constructor for class edu.cmu.tetrad.util.TextTable
Construct the text table; the table has a fixed number of rows and columns, each greater than zero.
TextTable.Delimiter - Enum Class in edu.cmu.tetrad.util
An enum of delimiters.
TeyssierScorer - Class in edu.cmu.tetrad.search.utils
Implements and extends a scorer extending Teyssier, M., and Koller, D.
TeyssierScorer(IndependenceTest, Score) - Constructor for class edu.cmu.tetrad.search.utils.TeyssierScorer
Constructor that takes both a test or a score.
THR - Static variable in class edu.cmu.tetrad.util.Params
Constant THR="thr"
threshold(Matrix, double) - Static method in class edu.cmu.tetrad.search.IcaLingD
Thresholds the given matrix, sending any small entries in absolute value to zero.
Threshold - Enum constant in enum class edu.pitt.dbmi.algo.resampling.ResamplingEdgeEnsemble
Choose an edge iff its prob.
THRESHOLD_B - Static variable in class edu.cmu.tetrad.util.Params
Constant THRESHOLD_B="thresholdBHat"
THRESHOLD_FOR_NUM_EIGENVALUES - Static variable in class edu.cmu.tetrad.util.Params
Constant THRESHOLD_FOR_NUM_EIGENVALUES="thresholdForNumEigenvalues"
THRESHOLD_NO_RANDOM_CONSTRAIN_SEARCH - Static variable in class edu.cmu.tetrad.util.Params
Constant THRESHOLD_NO_RANDOM_CONSTRAIN_SEARCH="thresholdNoRandomConstrainSearch"
THRESHOLD_NO_RANDOM_DATA_SEARCH - Static variable in class edu.cmu.tetrad.util.Params
Constant THRESHOLD_NO_RANDOM_DATA_SEARCH="thresholdNoRandomDataSearch"
THRESHOLD_W - Static variable in class edu.cmu.tetrad.util.Params
Constant THRESHOLD_SPINE="thresholdSpine"
TIME_LAG - Static variable in class edu.cmu.tetrad.util.Params
Constant TIME_LAG="timeLag"
TIME_SERIES - Static variable in class edu.cmu.tetrad.algcomparison.simulation.SimulationTypes
Constant TIME_SERIES="Time Series"
TimeLagGraph - Class in edu.cmu.tetrad.graph
Represents a time series graph--that is, a graph with a fixed number S of lags, with edges into initial lags only--that is, into nodes in the first R lags, for some R.
TimeLagGraph() - Constructor for class edu.cmu.tetrad.graph.TimeLagGraph
Constructor for TimeLagGraph.
TimeLagGraph(TimeLagGraph) - Constructor for class edu.cmu.tetrad.graph.TimeLagGraph
Constructor for TimeLagGraph.
TimeLagGraph.NodeId - Class in edu.cmu.tetrad.graph
Represents a NodeId with a name and a lag value.
timeMillis() - Static method in class edu.cmu.tetrad.util.MillisecondTimes
timeMillis.
TIMEOUT - Static variable in class edu.cmu.tetrad.util.Params
Constant TIMEOUT="timeout"
TimeoutComparison - Class in edu.cmu.tetrad.algcomparison
Nov 14, 2017 12:00:31 PM
TimeoutComparison() - Constructor for class edu.cmu.tetrad.algcomparison.TimeoutComparison
Represents a comparison of two time values for timeout purposes.
TimeoutComparison.ComparisonGraph - Enum Class in edu.cmu.tetrad.algcomparison
An enum of graph types to compare.
times(Matrix) - Method in class edu.cmu.tetrad.util.Matrix
times.
times(Vector) - Method in class edu.cmu.tetrad.util.Matrix
times.
TimeSeries - Annotation Interface in edu.cmu.tetrad.annotation
Aug 7, 2019 6:17:29 PM
TimeSeriesData - Class in edu.cmu.tetrad.data
Stores time series data as a list of continuous columns.
TimeSeriesData(Matrix, List<String>) - Constructor for class edu.cmu.tetrad.data.TimeSeriesData
Constructs a new time series data contains for the given row-major data array and the given list of variables.
TimeSeriesSemSimulation - Class in edu.cmu.tetrad.algcomparison.simulation
Time series SEM simulation.
TimeSeriesSemSimulation(RandomGraph) - Constructor for class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
Constructor for TimeSeriesSemSimulation.
tippett - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Tippett's method
tippett - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
The tippett method.
tKeys() - Method in class edu.cmu.tetrad.search.utils.AlmostCycleRemover
Returns the set of nodes that are keys in the map of triples.
toArray() - Method in class edu.cmu.tetrad.simulation.PRAOerrors
toArray.
toArray() - Method in class edu.cmu.tetrad.util.Matrix
toArray.
toArray() - Method in class edu.cmu.tetrad.util.Vector
toArray.
toContinuousDataModel(ContinuousData) - Static method in class edu.cmu.tetrad.util.DataConvertUtils
toContinuousDataModel.
toCovarianceMatrix(CovarianceData) - Static method in class edu.cmu.tetrad.util.DataConvertUtils
toCovarianceMatrix.
toDataModel(Data) - Static method in class edu.cmu.tetrad.util.DataConvertUtils
toDataModel.
toDataModel(Data, Metadata) - Static method in class edu.cmu.tetrad.util.DataConvertUtils
toDataModel.
toDelimiter(char) - Static method in class edu.cmu.tetrad.util.DelimiterUtils
Get the enum delimiter corresponding to char delimiter: tab, space, comma, colon, semicolon, pipe.
Token - Enum Class in edu.cmu.tetrad.calculator.parser
Allowable tokens.
toMatrix1D() - Method in class edu.pitt.csb.mgm.Mgm.MGMParams
Copy all params into a single vector
toMixedDataBox(MixedTabularData) - Static method in class edu.cmu.tetrad.util.DataConvertUtils
toMixedDataBox.
toMixedDataBox(MixedTabularData, Metadata) - Static method in class edu.cmu.tetrad.util.DataConvertUtils
Converting using metadata
toNodes(DataColumn[]) - Static method in class edu.cmu.tetrad.util.DataConvertUtils
toNodes.
toNodes(DiscreteDataColumn[]) - Static method in class edu.cmu.tetrad.util.DataConvertUtils
toNodes.
toNodes(List<String>) - Static method in class edu.cmu.tetrad.util.DataConvertUtils
toNodes.
TOP_BRACKET - Static variable in class edu.cmu.tetrad.util.Params
Constant TOP_BRACKET="topBracket"
topEigenvalues() - Method in record class edu.cmu.tetrad.search.test.Kci.EigenReturn
Returns the value of the topEigenvalues record component.
TopEigenvalues - Class in edu.cmu.tetrad.search.test
The class is used to find the top eigenvalues and eigenvectors of a given matrix.
TopEigenvalues(SimpleMatrix) - Constructor for class edu.cmu.tetrad.search.test.TopEigenvalues
Construct a new object with the given matrix.
topToBottomLayout(TimeLagGraph) - Static method in class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation
topToBottomLayout.
toString() - Method in class edu.cmu.tetrad.annotation.AnnotatedClass
 
toString() - Method in class edu.cmu.tetrad.bayes.ApproximateUpdater
Prints out the most recent marginal.
toString() - Method in interface edu.cmu.tetrad.bayes.BayesIm
Returns a string representation for this Bayes net.
toString() - Method in class edu.cmu.tetrad.bayes.BayesPm
Prints out the list of values for each node.
toString() - Method in class edu.cmu.tetrad.bayes.CptInvariantUpdater
Prints out the most recent marginal.
toString() - Method in class edu.cmu.tetrad.bayes.DirichletBayesIm
Prints out the probability table for each variable.
toString() - Method in class edu.cmu.tetrad.bayes.Evidence
toString.
toString() - Method in class edu.cmu.tetrad.bayes.Identifiability
toString.
toString() - Method in class edu.cmu.tetrad.bayes.JunctionTreeAlgorithm
toString() - Method in class edu.cmu.tetrad.bayes.JunctionTreeUpdater
toString() - Method in class edu.cmu.tetrad.bayes.Manipulation
toString.
toString() - Method in class edu.cmu.tetrad.bayes.MlBayesIm
Prints out the probability table for each variable.
toString() - Method in class edu.cmu.tetrad.bayes.MlBayesImObs
Prints out the probability table for each variable.
toString() - Method in class edu.cmu.tetrad.bayes.Proposition
toString.
toString() - Method in class edu.cmu.tetrad.bayes.RowSummingExactUpdater
Prints out the most recent marginal.
toString() - Method in class edu.cmu.tetrad.bayes.StoredCellProbs
toString.
toString() - Method in class edu.cmu.tetrad.bayes.StoredCellProbsObs
toString.
toString() - Method in class edu.cmu.tetrad.bayes.UpdatedBayesIm
Prints out the probability table for each variable.
toString() - Method in class edu.cmu.tetrad.calculator.expression.ConstantExpression
toString.
toString() - Method in class edu.cmu.tetrad.calculator.expression.VariableExpression
toString.
toString() - Method in class edu.cmu.tetrad.cluster.KMeans
toString.
toString() - Method in class edu.cmu.tetrad.data.AbstractVariable
toString.
toString() - Method in class edu.cmu.tetrad.data.BoxDataSet
toString.
toString() - Method in class edu.cmu.tetrad.data.Clusters
toString.
toString() - Method in class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly
Prints out the matrix
toString() - Method in class edu.cmu.tetrad.data.CovarianceMatrix
Prints out the matrix
toString() - Method in class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly
Prints out the matrix
toString() - Method in interface edu.cmu.tetrad.data.DataModel
Renders the data model as as String.
toString() - Method in class edu.cmu.tetrad.data.DataModelList
toString.
toString() - Method in interface edu.cmu.tetrad.data.DataSet
toString.
toString() - Method in class edu.cmu.tetrad.data.DelimiterType
Prints out the name of the type.
toString() - Method in class edu.cmu.tetrad.data.DiscreteVariable
toString.
toString() - Method in class edu.cmu.tetrad.data.DiscreteVariableType
Prints out the name of the type.
toString() - Method in class edu.cmu.tetrad.data.Discretizer.Discretization
Returns a string representation of the Discretization object.
toString() - Method in interface edu.cmu.tetrad.data.ICovarianceMatrix
Renders the covariance matrix as a string representation.
toString() - Method in class edu.cmu.tetrad.data.IndependenceFacts
toString.
toString() - Method in class edu.cmu.tetrad.data.Knowledge
toString.
toString() - Method in class edu.cmu.tetrad.data.KnowledgeEdge
toString.
toString() - Method in class edu.cmu.tetrad.data.NumberObjectDataSet
toString.
toString() - Method in class edu.cmu.tetrad.graph.Dag
toString.
toString() - Method in class edu.cmu.tetrad.graph.Edge
Produces a string representation of the edge.
toString() - Method in class edu.cmu.tetrad.graph.EdgeListGraph
toString.
toString() - Method in interface edu.cmu.tetrad.graph.Graph
toString.
toString() - Method in class edu.cmu.tetrad.graph.GraphNode
toString.
toString() - Method in class edu.cmu.tetrad.graph.GraphUtils.TwoCycleErrors
Returns a string representation of this object.
toString() - Method in class edu.cmu.tetrad.graph.IndependenceFact
toString.
toString() - Method in interface edu.cmu.tetrad.graph.Node
Returns the intervention type for this node.
toString() - Method in class edu.cmu.tetrad.graph.NodePair
toString.
toString() - Method in class edu.cmu.tetrad.graph.OrderedPair
toString.
toString() - Method in class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
A string representation of the structural information for the generated graph.
toString() - Method in class edu.cmu.tetrad.graph.SemGraph
toString.
toString() - Method in class edu.cmu.tetrad.graph.TimeLagGraph
toString.
toString() - Method in class edu.cmu.tetrad.graph.Triple
toString.
toString() - Method in class edu.cmu.tetrad.regression.LogisticRegression.Result
Returns a string representation of the regression results.
toString() - Method in class edu.cmu.tetrad.regression.RegressionResult
toString.
toString() - Method in class edu.cmu.tetrad.search.FastIca.IcaResult
Returns a string representation of this IcaResult object.
toString() - Method in class edu.cmu.tetrad.search.FciOrientDijkstra.DijkstraEdge
Returns a string representation of the DijkstraEdge.
toString() - Method in class edu.cmu.tetrad.search.Ida.NodeEffects
Returns a string representation of this object.
toString() - Method in interface edu.cmu.tetrad.search.IndependenceTest
Returns a string representation of this test.
toString() - Method in class edu.cmu.tetrad.search.IndTestIod
Returns a string representation of this test.
toString() - Method in record class edu.cmu.tetrad.search.MarkovCheck.MarkovCheckRecord
Returns a string representation of this record class.
toString() - Method in class edu.cmu.tetrad.search.score.BasisFunctionBicScore
Returns a string representation of the BasisFunctionBicScore object.
toString() - Method in class edu.cmu.tetrad.search.score.BdeScore
Returns a string representation of the object.
toString() - Method in class edu.cmu.tetrad.search.score.BdeuScore
Returns a string representation of this BDeu Score object.
toString() - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianLikelihood.Ret
Returns a string representation of this object.
toString() - Method in class edu.cmu.tetrad.search.score.ConditionalGaussianScore
A string representation of the score.
toString() - Method in class edu.cmu.tetrad.search.score.DegenerateGaussianScore
A string representation of the score.
toString() - Method in class edu.cmu.tetrad.search.score.DiscreteBicScore
A string representation of the score.
toString() - Method in class edu.cmu.tetrad.search.score.DiscreteBicScoreAdTree
A string representation of the score.
toString() - Method in class edu.cmu.tetrad.search.score.GicScores
Returns a string for this object.
toString() - Method in interface edu.cmu.tetrad.search.score.Score
A string representation of the score.
toString() - Method in record class edu.cmu.tetrad.search.score.SemBicScore.CovAndCoefs
Returns a string representation of this record class.
toString() - Method in class edu.cmu.tetrad.search.score.SemBicScore
Returns a string representation of this score.
toString() - Method in class edu.cmu.tetrad.search.test.IndependenceResult
Returns a string representation of this independence fact.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestChiSquare
Returns a string representation of this test.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalCorrelation
Returns a string representation of this test.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt
Returns a string representation of this test.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt.Ret
Returns a string representation of this object.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt
Returns a string representation of this test.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZ
Returns a string representation of the Fisher Z independence test.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZConcatenateResiduals
Returns a string representation of the object.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestFisherZFisherPValue
Returns a string representation of this test.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestGSquare
Returns a String representation of this test.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestHsic
Returns a string representation of this test.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestMulti
Returns a string representation of this object, which includes the alpha value of the independence test.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestRegression
Returns a string representation of the Linear Regression Test object.
toString() - Method in class edu.cmu.tetrad.search.test.IndTestTrekSep
Returns a string representation of this test.
toString() - Method in record class edu.cmu.tetrad.search.test.Kci.EigenReturn
Returns a string representation of this record class.
toString() - Method in class edu.cmu.tetrad.search.test.Kci
Returns a string representation of this test.
toString() - Method in class edu.cmu.tetrad.search.test.MsepTest
Returns a string representation of this test.
toString() - Method in class edu.cmu.tetrad.search.test.ScoreIndTest
Returns a string representation of the object.
toString() - Method in class edu.cmu.tetrad.search.utils.Bes.Arrow
Returns the index of the arrow.
toString() - Method in class edu.cmu.tetrad.search.utils.DiscriminatingPath
 
toString() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms.GraphoidIndFact
Returns a string representation of this object.
toString() - Method in class edu.cmu.tetrad.search.utils.PermutationMatrixPair
Prints a string representation of this.
toString() - Method in class edu.cmu.tetrad.search.utils.PossibleMConnectingPath
toString.
toString() - Method in class edu.cmu.tetrad.search.utils.R5R9Dijkstra.DijkstraEdge
Returns a string representation of the DijkstraEdge object.
toString() - Method in class edu.cmu.tetrad.search.utils.SepsetMap
Returns a string representation of this sepset map.
toString() - Method in class edu.cmu.tetrad.search.utils.Sextad
toString.
toString() - Method in class edu.cmu.tetrad.search.utils.Tetrad
toString.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.DMSearch.LatentStructure
toString.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Anly outputs ops which have elements, not empty structures.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move
Returns a string representation of this move.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestCramerT
Returns a string representation of the object.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZPercentIndependent
Returns a string representation of this object.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestFisherZRecursive
toString.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMixedMultipleTTest
Returns a string representation of the object.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMnlrLr
Returns a string representation of this object.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestMultinomialLogisticRegression
Returns a string representation of the object.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestPositiveCorr
Returns a string representation of the Fisher Z object.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.IndTestSepsetDci
toString.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.MagCgBicScore
toString.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.MagDgBicScore
toString.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.MagSemBicScore
toString.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.SepsetMapDci
toString.
toString() - Method in class edu.cmu.tetrad.search.work_in_progress.Sextad
toString.
toString() - Method in class edu.cmu.tetrad.sem.DagScorer
toString.
toString() - Method in class edu.cmu.tetrad.sem.GeneralizedSemIm
Returns a string representation of the object.
toString() - Method in class edu.cmu.tetrad.sem.GeneralizedSemPm
Returns a relatively brief String representation of this SEM PM--the equations and distributions of the model.
toString() - Method in class edu.cmu.tetrad.sem.Mapping
toString.
toString() - Method in enum class edu.cmu.tetrad.sem.ParamComparison
 
toString() - Method in enum class edu.cmu.tetrad.sem.ParamConstraintType
 
toString() - Method in class edu.cmu.tetrad.sem.Parameter
toString.
toString() - Method in enum class edu.cmu.tetrad.sem.ParamType
 
toString() - Method in class edu.cmu.tetrad.sem.Ricf.FitConGraphResult
Returns a string representation of the FitConGraphResult object.
toString() - Method in class edu.cmu.tetrad.sem.Ricf.RicfResult
Returns a string representation of the RicfResult object.
toString() - Method in interface edu.cmu.tetrad.sem.Scorer
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemEstimator
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemEstimatorGibbs
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemEvidence
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemIm
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemManipulation
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemOptimizerEm
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemOptimizerPowell
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemOptimizerRegression
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemOptimizerRicf
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemOptimizerScattershot
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemPm
toString.
toString() - Method in class edu.cmu.tetrad.sem.SemProposition
Returns a string representation of the object.
toString() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm.ParameterRange
toString.
toString() - Method in class edu.cmu.tetrad.sem.StandardizedSemIm
toString.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.biolingua.BiolinguaDigraph
Returns a specially formatted string with all the contents of this Graph.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicGraph
Returns a specially formatted string with all the contents of this Graph.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicLTMatrix
Returns a specially formatted string with all the contents of this matrix
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.BasicMatrix
Returns a specially formatted string with all the contents of this matrix
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.LTMatrix
Returns a specially formatted string with all the contents of this matrix
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.Matrix
Returns a specially formatted string with all the contents of this matrix
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrix
Returns a specially formatted string with all the contents of this matrix
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.util.SymMatrixF
Returns a specially formatted string with all the contents of this matrix
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph
toString.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph
Returns a string representation of the graph, indicating for each factor which lagged factors map into it.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction
Returns a string representation of the boolean function.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity
Returns a string representation of the graph, indicating for each factor which lagged factors map into it.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph
Returns a string representation of the graph, indicating for each factor which lagged factors map into it.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedParent
Prints out the factor index and lag.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedFactor
Returns a string representing this lagged factor.
toString() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.history.LagGraph
Returns a string representation of the graph, indicating for each factor which lagged factors map into it.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction
Prints out the linear function of each factor of its parents.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.Polynomial
Prints out a representation of the term.
toString() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialTerm
Prints out a representation of the term.
toString() - Method in class edu.cmu.tetrad.study.performance.ComparisonParameters
toString.
toString() - Method in class edu.cmu.tetrad.study.performance.ComparisonResult
toString.
toString() - Method in class edu.cmu.tetrad.util.DefaultTetradLoggerConfig.DefaultEvent
toString.
toString() - Method in class edu.cmu.tetrad.util.DefaultTetradLoggerConfig
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.Beta
A string representation of the distribution.
toString() - Method in class edu.cmu.tetrad.util.dist.ChiSquare
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.Discrete
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.Exponential
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.Gamma
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.Indicator
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.LogNormal
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.MixtureOfGaussians
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.Normal
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.Poisson
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.SingleValue
Returns a string representation of the object.
toString() - Method in class edu.cmu.tetrad.util.dist.Split
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.TruncatedNormal
toString.
toString() - Method in class edu.cmu.tetrad.util.dist.Uniform
toString.
toString() - Method in interface edu.cmu.tetrad.util.Function
toString.
toString() - Method in class edu.cmu.tetrad.util.Matrix
toString.
toString() - Method in class edu.cmu.tetrad.util.Parameters
toString() - Method in class edu.cmu.tetrad.util.PartialCorrelationPdf
toString.
toString() - Method in class edu.cmu.tetrad.util.Point
toString.
toString() - Method in class edu.cmu.tetrad.util.PointXy
toString.
toString() - Method in class edu.cmu.tetrad.util.SublistGenerator
toString.
toString() - Method in interface edu.cmu.tetrad.util.TetradLoggerConfig
Returns a string representation of the object.
toString() - Method in class edu.cmu.tetrad.util.TextTable
toString.
toString() - Method in class edu.cmu.tetrad.util.Vector
toString.
toString() - Method in class edu.cmu.tetrad.util.Version
toString.
toString() - Method in class edu.pitt.csb.mgm.IndTestMultinomialLogisticRegressionWald
Returns a string representation of the object.
toString() - Method in class edu.pitt.csb.mgm.Mgm.MGMParams
Returns a string representation of the object
toString(boolean[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Copies the given array, starting each line with a tab character..
toString(double[]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
toString.
toString(double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
Copies the given array, using a standard scientific notation number formatter and beginning each line with a tab character.
toString(double[][], List<String>) - Static method in class edu.cmu.tetrad.util.MatrixUtils
toString.
toString(double[], NumberFormat) - Static method in class edu.cmu.tetrad.util.MatrixUtils
toString.
toString(int[]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
toString.
toString(int[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
toString.
toString(int[][], List<String>) - Static method in class edu.cmu.tetrad.util.MatrixUtils
toString.
toStringDep() - Method in class edu.cmu.tetrad.search.MarkovCheck.AllSubsetsIndependenceFacts
Returns a string representation of the m-connection facts.
toStringIndep() - Method in class edu.cmu.tetrad.search.MarkovCheck.AllSubsetsIndependenceFacts
Returns a string representation of the m-separation facts.
toStringSquare(double[][], NumberFormat, List<String>) - Static method in class edu.cmu.tetrad.util.MatrixUtils
toStringSquare.
toStringSquare(double[][], List<String>) - Static method in class edu.cmu.tetrad.util.MatrixUtils
toStringSquare.
toStringSquare(int[][], List<String>) - Static method in class edu.cmu.tetrad.util.MatrixUtils
toStringSquare.
totalInstabilityDir(DoubleMatrix2D, List<Node>) - Static method in class edu.pitt.csb.stability.StabilityUtils
totalInstabilityDir.
totalInstabilityUndir(DoubleMatrix2D, List<Node>) - Static method in class edu.pitt.csb.stability.StabilityUtils
totalInstabilityUndir.
toVerticalDiscreteDataModel(VerticalDiscreteTabularData) - Static method in class edu.cmu.tetrad.util.DataConvertUtils
toVerticalDiscreteDataModel.
toVerticalDiscreteDataModel(VerticalDiscreteTabularData, Metadata) - Static method in class edu.cmu.tetrad.util.DataConvertUtils
Converting using metadata
toXML() - Method in class edu.pitt.isp.sverchkov.data.AdTree
Converts to XML.
toXML(DocumentBuilder) - Method in class edu.pitt.isp.sverchkov.data.AdTree
Converts to XML.
tPdf(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
tPdf.
tQuantile(double, double) - Static method in class edu.cmu.tetrad.util.ProbUtils
CACM Algorithm 396, by G.
trace() - Method in class edu.cmu.tetrad.util.Matrix
trace.
trace(double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
trace.
trace(Set<Node>, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
trace.
trace(Set<Node>, Set<Node>, Set<Node>) - Method in class edu.cmu.tetrad.search.utils.GrowShrinkTree
trace.
tRand(double) - Static method in class edu.cmu.tetrad.util.ProbUtils
T distribution random generator.
transferAttributes(Graph) - Method in class edu.cmu.tetrad.graph.Dag
Transfers attributes from the given graph to the current graph.
transferAttributes(Graph) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
transferAttributes.
transferAttributes(Graph) - Method in interface edu.cmu.tetrad.graph.Graph
transferAttributes.
transferAttributes(Graph) - Method in class edu.cmu.tetrad.graph.LagGraph
transferAttributes.
transferAttributes(Graph) - Method in class edu.cmu.tetrad.graph.SemGraph
transferAttributes.
transferAttributes(Graph) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Transfers attributes from the given graph to the current graph.
transferNodesAndEdges(Graph) - Method in class edu.cmu.tetrad.graph.Dag
Transfers nodes and edges from the given graph to the current graph.
transferNodesAndEdges(Graph) - Method in class edu.cmu.tetrad.graph.EdgeListGraph
Transfers nodes and edges from one graph to another.
transferNodesAndEdges(Graph) - Method in interface edu.cmu.tetrad.graph.Graph
Transfers nodes and edges from one graph to another.
transferNodesAndEdges(Graph) - Method in class edu.cmu.tetrad.graph.LagGraph
Transfers nodes and edges from one graph to another.
transferNodesAndEdges(Graph) - Method in class edu.cmu.tetrad.graph.SemGraph
Transfers nodes and edges from one graph to another.
transferNodesAndEdges(Graph) - Method in class edu.cmu.tetrad.graph.TimeLagGraph
Transfers nodes and edges from the given graph to the current graph.
transform(DataSet, String...) - Static method in class edu.cmu.tetrad.calculator.Transformation
Transforms the given data using the given representations of transforming equations.
Transformation - Class in edu.cmu.tetrad.calculator
Represents a transformation on some dataset.
transformCpdagIntoRandomDag(Graph, Knowledge, boolean, boolean) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Transforms a completed partially directed acyclic graph (CPDAG) into a random directed acyclic graph (DAG) by randomly orienting the undirected edges in the CPDAG in shuffled order.
translate(String, List<Node>) - Static method in class edu.cmu.tetrad.search.utils.GraphSearchUtils
translate.
transormPagIntoRandomMag(Graph) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Transforms a partially ancestral graph (PAG) into a maximally ancestral graph (MAG) by randomly orienting the circle endpoints as either tail or arrow and then applying the final FCI orient algorithm after each change.
transpose() - Method in class edu.cmu.tetrad.util.Matrix
transpose.
transpose(double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
transpose.
transposeWithoutCopy(RealMatrix) - Static method in class edu.cmu.tetrad.util.MatrixUtils
transposeWithoutCopy.
traverse(Node, Edge) - Static method in class edu.cmu.tetrad.graph.Edges
If node is one endpoint of edge, returns the other endpoint.
traverseDirected(Node, Edge) - Static method in class edu.cmu.tetrad.graph.Edges
For A -> B, given A, returns B; otherwise returns null.
traverseNondirected(Node, Edge) - Static method in class edu.cmu.tetrad.graph.Edges
For A o-o B, given A, returns B; otherwise returns null.
traverseReverseDirected(Node, Edge) - Static method in class edu.cmu.tetrad.graph.Edges
For A -> B, given B, returns A; otherwise returns null.
traverseSemiDirected(Node, Edge) - Static method in class edu.cmu.tetrad.graph.Edges
For A --* B or A o-* B, given A, returns B.
traverseSemiDirected(Node, Edge) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Traverses a semi-directed edge to identify the next node in the traversal.
treks(Graph, Node, Node) - Static method in class edu.cmu.tetrad.search.work_in_progress.Ion
treks.
treks(Node, Node, int) - Method in class edu.cmu.tetrad.graph.Paths
Finds all treks from node1 to node2 with a maximum length.
treksIncludingBidirected(Node, Node) - Method in class edu.cmu.tetrad.graph.Paths
Finds all possible treks between two nodes, including bidirectional treks.
triangle(Node, Node, Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns true iff [a, b, c] is a triangle.
trimEdgesAmongParents(Graph, Node) - Static method in class edu.cmu.tetrad.search.utils.MbUtils
Removes edges among the parents of the target.
trimEdgesAmongParentsOfChildren(Graph, Node) - Static method in class edu.cmu.tetrad.search.utils.MbUtils
Removes edges among the parents of children of the target.
trimGraph(List<Node>, Graph, int) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Trims the given graph based on the specified trimming style.
TRIMMING_STYLE - Static variable in class edu.cmu.tetrad.util.Params
Constant TRIMMING_STYLE="trimmingStyle"
trimToAdjacents(Graph, Node) - Static method in class edu.cmu.tetrad.search.utils.MbUtils
Trims the graph to just the adjacents of the target.
trimToMbNodes(Graph, Node, boolean) - Static method in class edu.cmu.tetrad.search.utils.MbUtils
Trims the graph to the target, the parents and children of the target, and the parents of the children of the target.
triple(Graph, Node, Node, Node) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Checks if three nodes are connected in a graph.
Triple - Class in edu.cmu.tetrad.graph
Stores a triple (x, y, z) of nodes.
Triple(Node, Node, Node) - Constructor for class edu.cmu.tetrad.graph.Triple
Constructs a triple of nodes.
tripleAllowed(Node, Node, Node) - Method in class edu.cmu.tetrad.search.utils.AlmostCycleRemover
Determines whether a triple consisting of three given nodes is allowed.
TripleClassifier - Interface in edu.cmu.tetrad.graph
Marks a search algorithm as a triad classifier and returns the triad classifications if makes.
triplesToText(Set<Triple>, String) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts a set of triples into a formatted string.
true_DAG - Enum constant in enum class edu.cmu.tetrad.algcomparison.Comparison.ComparisonGraph
Constant for the true DAG.
true_DAG - Enum constant in enum class edu.cmu.tetrad.algcomparison.TimeoutComparison.ComparisonGraph
The true dag.
TrueDagFalseNegativesArrows - Class in edu.cmu.tetrad.algcomparison.statistic
Represents the statistic of False Negatives for Arrows compared to the true DAG.
TrueDagFalseNegativesArrows() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesArrows
Constructs the statistic.
TrueDagFalseNegativesTails - Class in edu.cmu.tetrad.algcomparison.statistic
The class TrueDagFalseNegativesTails implements the Statistic interface to calculate the number of false negatives for tails compared to the true Directed Acyclic Graph (DAG).
TrueDagFalseNegativesTails() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesTails
Constructs the statistic.
TrueDagFalsePositiveArrow - Class in edu.cmu.tetrad.algcomparison.statistic
Represents a statistic that calculates the false positives for arrows compared to the true directed acyclic graph (DAG).
TrueDagFalsePositiveArrow() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveArrow
This class represents a statistic that calculates the false positives for arrows compared to the true DAG.
TrueDagFalsePositiveTails - Class in edu.cmu.tetrad.algcomparison.statistic
TrueDagFalsePositiveTails is a class that implements the Statistic interface.
TrueDagFalsePositiveTails() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveTails
Constructs a new TrueDagFalsePositiveTails object.
TrueDagPrecisionArrow - Class in edu.cmu.tetrad.algcomparison.statistic
The proportion of X*->Y in the estimated graph for which there is no path Y~~>X in the true graph.
TrueDagPrecisionArrow() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionArrow
This class represents a statistic that calculates the precision for arrows compared to the true DAG.
TrueDagPrecisionTails - Class in edu.cmu.tetrad.algcomparison.statistic
A class that implements the Statistic interface to calculate the proportion of X-->Y edges in the estimated graph for which there is a path X~~>Y in the true graph.
TrueDagPrecisionTails() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionTails
This class represents a statistic that calculates the precision for tails compared to the true DAG.
TrueDagRecallArrows - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
TrueDagRecallArrows() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallArrows
This class represents a statistic that calculates the recall for arrows compared to the true DAG.
TrueDagRecallTails - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
TrueDagRecallTails() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallTails
This class represents a statistic that calculates the true positives for tails compared to the true DAG.
TrueDagTruePositiveArrow - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
TrueDagTruePositiveArrow() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveArrow
This class represents a statistic that calculates the true positives for arrows compared to the true DAG.
TrueDagTruePositiveDirectedPathNonancestor - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
TrueDagTruePositiveDirectedPathNonancestor() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveDirectedPathNonancestor
This class represents a statistic that calculates the true positives for arrows compared to the true DAG.
TrueDagTruePositiveTails - Class in edu.cmu.tetrad.algcomparison.statistic
The bidirected true positives.
TrueDagTruePositiveTails() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveTails
This class represents a statistic that calculates the true positives for tails compared to the true DAG.
TruncatedNormal - Class in edu.cmu.tetrad.util.dist
A normal distribution that allows its parameters to be set and allows random sampling.
TRUNCATION_LIMIT - Static variable in class edu.cmu.tetrad.util.Params
Constant TRUNCATION_LIMIT="truncationLimit"
TsDagToPag - Class in edu.cmu.tetrad.search.utils
Finds the PAG to which a DAG belongs, for a time series model.
TsDagToPag(Graph) - Constructor for class edu.cmu.tetrad.search.utils.TsDagToPag
Constructs a new FCI search for the given independence test and background knowledge.
TsUtils - Class in edu.cmu.tetrad.search.utils
Contains some utilities for doing autoregression.
TsUtils.VarResult - Class in edu.cmu.tetrad.search.utils
Gives a result consisting of the residuals and collapsed var graphs.
tt - Enum constant in enum class edu.cmu.tetrad.graph.EdgeTypeProbability.EdgeType
Tail-to-tail
tuck(Node, Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Moves j to before k and moves all the ancestors of j betwween k and j to before k.
tuck(Node, Node...) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Moves all j's to before k and moves all the ancestors of all ji's betwween k and ji to before k.
TWO_CYCLE_ALPHA - Static variable in class edu.cmu.tetrad.util.Params
Constant TWO_CYCLE_ALPHA="twoCycleAlpha"
TWO_CYCLE_SCREENING_THRESHOLD - Static variable in class edu.cmu.tetrad.util.Params
Constant TWO_CYCLE_SCREENING_THRESHOLD="twoCycleScreeningThreshold"
twoCycCor - Variable in class edu.cmu.tetrad.graph.GraphUtils.TwoCycleErrors
The number of correct edges.
twoCycFn - Variable in class edu.cmu.tetrad.graph.GraphUtils.TwoCycleErrors
The number of false negatives.
twoCycFp - Variable in class edu.cmu.tetrad.graph.GraphUtils.TwoCycleErrors
The number of false positives.
TwoCycleErrors(int, int, int) - Constructor for class edu.cmu.tetrad.graph.GraphUtils.TwoCycleErrors
Constructs a new TwoCycleErrors.
TwoCycleFalseNegative - Class in edu.cmu.tetrad.algcomparison.statistic
The 2-cycle precision.
TwoCycleFalseNegative() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalseNegative
This class represents a statistic that calculates the 2-cycle false negative.
TwoCycleFalsePositive - Class in edu.cmu.tetrad.algcomparison.statistic
The 2-cycle precision.
TwoCycleFalsePositive() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalsePositive
This class represents a statistic that calculates the 2-cycle precision.
TwoCyclePrecision - Class in edu.cmu.tetrad.algcomparison.statistic
The 2-cycle precision.
TwoCyclePrecision() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TwoCyclePrecision
This class represents a statistic that calculates the 2-cycle precision.
TwoCycleRecall - Class in edu.cmu.tetrad.algcomparison.statistic
The 2-cycle recall.
TwoCycleRecall() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TwoCycleRecall
This class represents a statistic that calculates the 2-cycle recall.
TwoCycleTruePositive - Class in edu.cmu.tetrad.algcomparison.statistic
The 2-cycle precision.
TwoCycleTruePositive() - Constructor for class edu.cmu.tetrad.algcomparison.statistic.TwoCycleTruePositive
The TwoCycleTruePositive class represents a statistic that calculates the number of true positives for 2-cycles in both the true and estimated graphs.
twoFactorTest(int, int, int, int) - Method in interface edu.cmu.tetrad.search.utils.TetradTest
twoFactorTest.
twoFactorTest(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
twoFactorTest.
twoFactorTest(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
twoFactorTest.
twoFactorTest(int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
twoFactorTest.
twoFactorTest(int, int, int, int, int) - Method in interface edu.cmu.tetrad.search.utils.TetradTest
twoFactorTest.
twoFactorTest(int, int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
twoFactorTest.
twoFactorTest(int, int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
twoFactorTest.
twoFactorTest(int, int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
twoFactorTest.
twoFactorTest(int, int, int, int, int, int) - Method in interface edu.cmu.tetrad.search.utils.TetradTest
twoFactorTest.
twoFactorTest(int, int, int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestContinuous
twoFactorTest.
twoFactorTest(int, int, int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
twoFactorTest.
twoFactorTest(int, int, int, int, int, int) - Method in class edu.cmu.tetrad.search.utils.TetradTestPopulation
twoFactorTest.
type - Static variable in class edu.cmu.tetrad.util.MillisecondTimes
Constant type

U

Underlines - Class in edu.cmu.tetrad.graph
Underlines class.
Underlines(Graph) - Constructor for class edu.cmu.tetrad.graph.Underlines
Constructor for Underlines.
Underlines(Underlines) - Constructor for class edu.cmu.tetrad.graph.Underlines
Constructor for Underlines.
undirectedEdge(Node, Node) - Static method in class edu.cmu.tetrad.graph.Edges
Constructs a new undirected edge from nodeA to nodeB (--).
undirectedGraph(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
undirectedGraph.
undirectedToBidirected(Graph) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Converts an undirected graph to a bidirected graph.
Uniform - Class in edu.cmu.tetrad.util.dist
For given a, b (a < b), returns a point chosen uniformly from [a, b].
Uniform(double, double) - Constructor for class edu.cmu.tetrad.util.dist.Uniform
Constructor for Uniform.
UniformGraphGenerator(int) - Constructor for class edu.cmu.tetrad.graph.RandomGraph.UniformGraphGenerator
Constructs a random graph generator for the given structure.
UniformityTest - Class in edu.cmu.tetrad.util
The UniformityTest class provides methods to calculate the p-value of a list of points using the Kolmogorov-Smirnov test and determine if the distribution is uniform.
UniformityTest() - Constructor for class edu.cmu.tetrad.util.UniformityTest
The UniformityTest class is used to calculate the p-value of a list of points using the Kolmogorov-Smirnov test and determine if the distribution is uniform.
uniformRand() - Static method in class edu.cmu.tetrad.util.ProbUtils
uniformRand.
uniformSeeds(long, long) - Static method in class edu.cmu.tetrad.util.ProbUtils
uniformSeeds.
union(GraphChange) - Method in class edu.cmu.tetrad.search.work_in_progress.GraphChange
Absorbs all changes from the GraphChange other into the calling GraphChange.
UNKNOWN - Enum constant in enum class edu.cmu.tetrad.calculator.parser.Token
Unknown.
Unmarshallable - Interface in edu.cmu.tetrad.util
Interface to tag classes that should not be cloned by marshalling.> 0
UnmeasuredConfounder - Annotation Interface in edu.cmu.tetrad.annotation
Sep 19, 2017 1:56:20 PM
unshieldedCollider(Graph, Node, Node, Node) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Checks if the given nodes are unshielded colliders when considering the given graph.
unshieldedCollider(Node, Node, Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns true iff [a, b, c] is an unshielded collider.
unshieldedTriple(Node, Node, Node) - Method in class edu.cmu.tetrad.search.utils.TeyssierScorer
Returns true iff [a, b, c] is an unshielded triple.
update() - Method in interface edu.cmu.tetrad.search.ModelObserver
This method is called when the model changes.
update() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.AbstractNbComponent
Updates.
update() - Method in interface edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbComponent
Updates.
update() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbFunction
update.
update() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbFunctionAnd
update.
update() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbFunctionOr
update.
update() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbFunctionSum
update.
update() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbFunctionSV
update.
update() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbGene
update.
update() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbGeneAnd
update.
update() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.algorithm.urchin.NbGeneOr
update.
update() - Method in class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory
Updates the history to the next time slice using some formula.
UpdatedBayesIm - Class in edu.cmu.tetrad.bayes
Represents a Bayes IM in which all of the conditional probability tables have been updated to take into account evidence.
UpdatedBayesIm(BayesIm) - Constructor for class edu.cmu.tetrad.bayes.UpdatedBayesIm
Constructs Bayes net in which CPT's updated for the given evidence are calculated on the fly.
UpdatedBayesIm(BayesIm, Evidence) - Constructor for class edu.cmu.tetrad.bayes.UpdatedBayesIm
Constructs Bayes net in which CPT's updated for the given evidence are calculated on the fly.
updatedIm(Matrix, Vector) - Method in class edu.cmu.tetrad.sem.SemIm
updatedIm.
UpdateFunction - Interface in edu.cmu.tetrad.study.gene.tetrad.gene.history
Implements a function from the previous time steps of a history array to the getModel time step.
UPPER_BOUND - Static variable in class edu.cmu.tetrad.util.Params
Constant UPPER_BOUND="upperBound"
upperTri(DoubleMatrix2D, int) - Static method in class edu.pitt.csb.mgm.Mgm
upperTri.
USE_BES - Static variable in class edu.cmu.tetrad.util.Params
Constant USE_BES="useBes"
USE_CORR_DIFF_ADJACENCIES - Static variable in class edu.cmu.tetrad.util.Params
Constant USE_CORR_DIFF_ADJACENCIES="useCorrDiffAdjacencies"
USE_DATA_ORDER - Static variable in class edu.cmu.tetrad.util.Params
Constant USE_DATA_ORDER="useDataOrder"
USE_FAS_ADJACENCIES - Static variable in class edu.cmu.tetrad.util.Params
Constant USE_FAS_ADJACENCIES="useFasAdjacencies"
USE_GAP - Static variable in class edu.cmu.tetrad.util.Params
Constant USE_GAP="useGap"
USE_MAX_P_HEURISTIC - Static variable in class edu.cmu.tetrad.util.Params
Constant USE_MAX_P_HEURISTIC="useMaxPHeuristic"
USE_MAX_P_ORIENTATION_HEURISTIC - Static variable in class edu.cmu.tetrad.util.Params
Constant USE_MAX_P_ORIENTATION_HEURISTIC="useMaxPOrientationHeuristic"
USE_PSEUDOINVERSE - Static variable in class edu.cmu.tetrad.util.Params
Constant USE_PSEUDOINVERSE="usePseudoinverse"
USE_SKEW_ADJACENCIES - Static variable in class edu.cmu.tetrad.util.Params
Constant USE_SKEW_ADJACENCIES="useSkewAdjacencies"
USE_WISHART - Static variable in class edu.cmu.tetrad.util.Params
Constant USE_WISHART="useWishart"
User - Enum constant in enum class edu.cmu.tetrad.util.MillisecondTimes.Type
User time.
userTimeMillis() - Static method in class edu.cmu.tetrad.util.MillisecondTimes
userTimeMillis.
UsesScoreWrapper - Interface in edu.cmu.tetrad.algcomparison.utils
Tags an algorithm as using a score wrapper.

V

V() - Method in record class edu.cmu.tetrad.search.test.Kci.EigenReturn
Returns the value of the V record component.
valSet(DoubleMatrix1D) - Static method in class edu.pitt.csb.mgm.MixedUtils
valSet.
valueAt(double) - Method in interface edu.cmu.tetrad.util.Function
valueAt.
valueAt(double) - Method in class edu.cmu.tetrad.util.PartialCorrelationPdf
valueAt.
valueAt(double...) - Method in interface edu.cmu.tetrad.sem.ConnectionFunction
valueAt.
valueOf(String) - Static method in enum class edu.cmu.tetrad.algcomparison.Comparison.ComparisonGraph
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.algcomparison.TimeoutComparison.ComparisonGraph
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.annotation.AlgType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.bayes.MlBayesIm.CptMapType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.bayes.MlBayesIm.InitializationMethod
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.calculator.expression.ExpressionDescriptor.Position
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.calculator.parser.ExpressionParser.RestrictionType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.calculator.parser.Token
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.data.DataType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.graph.Edge.Property
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.graph.EdgeTypeProbability.EdgeType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.graph.Endpoint
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.graph.GraphUtils.GraphType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.graph.NodeType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.graph.NodeVariableType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.ConditioningSetType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.CpdagParentDistancesFromTrue.DistanceType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.Cstar.CpdagAlgorithm
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.Cstar.SampleStyle
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.Fask.LeftRight
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.FaskOrig.AdjacencyMethod
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.FaskOrig.LeftRight
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.Fofc.Algorithm
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.Ftfc.Algorithm
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.Lofs.Rule
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.Lofs.Score
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.LvLite.ExtraEdgeRemovalStyle
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.LvLite.START_WITH
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.score.GicScores.RuleType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.score.SemBicScore.RuleType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.test.ChiSquareTest.CellTableType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.test.ChiSquareTest.TestType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.test.Kci.KernelType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.utils.BpcAlgorithmType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.utils.BpcTestType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.utils.ClusterSignificance.CheckType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.utils.GraphSearchUtils.CpcTripleType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.utils.PcCommon.ColliderDiscovery
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.utils.PcCommon.ConflictRule
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.utils.PcCommon.FasType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.utils.PcCommon.PcHeuristicType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased.BlockingType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.utils.R5R9Dijkstra.Rule
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move.Type
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.work_in_progress.VcPc.CpcTripleType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.search.work_in_progress.VcPcFast.CpcTripleType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.sem.ParamComparison
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.sem.ParamConstraintType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.sem.ParamType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.sem.ScoreType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.sem.StandardizedSemIm.Initialization
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.Algorithm
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.DataType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.IndependenceTestType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.ResultType
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.util.MillisecondTimes.Type
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.cmu.tetrad.util.TextTable.Delimiter
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCCausalInference.OP
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCInference.OP
Returns the enum constant of this class with the specified name.
valueOf(String) - Static method in enum class edu.pitt.dbmi.algo.resampling.ResamplingEdgeEnsemble
Returns the enum constant of this class with the specified name.
values() - Static method in enum class edu.cmu.tetrad.algcomparison.Comparison.ComparisonGraph
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.algcomparison.TimeoutComparison.ComparisonGraph
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.annotation.AlgType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.bayes.MlBayesIm.CptMapType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.bayes.MlBayesIm.InitializationMethod
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.calculator.expression.ExpressionDescriptor.Position
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.calculator.parser.ExpressionParser.RestrictionType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.calculator.parser.Token
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.data.DataType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.graph.Edge.Property
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.graph.EdgeTypeProbability.EdgeType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.graph.Endpoint
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.graph.GraphUtils.GraphType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.graph.NodeType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.graph.NodeVariableType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.ConditioningSetType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.CpdagParentDistancesFromTrue.DistanceType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.Cstar.CpdagAlgorithm
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.Cstar.SampleStyle
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.Fask.LeftRight
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.FaskOrig.AdjacencyMethod
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.FaskOrig.LeftRight
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.Fofc.Algorithm
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.Ftfc.Algorithm
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.Lofs.Rule
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.Lofs.Score
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.LvLite.ExtraEdgeRemovalStyle
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.LvLite.START_WITH
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.score.GicScores.RuleType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.score.SemBicScore.RuleType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.test.ChiSquareTest.CellTableType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.test.ChiSquareTest.TestType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.test.Kci.KernelType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.utils.BpcAlgorithmType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.utils.BpcTestType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.utils.ClusterSignificance.CheckType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.utils.GraphSearchUtils.CpcTripleType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.utils.PcCommon.ColliderDiscovery
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.utils.PcCommon.ConflictRule
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.utils.PcCommon.FasType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.utils.PcCommon.PcHeuristicType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.utils.R0R4StrategyTestBased.BlockingType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.utils.R5R9Dijkstra.Rule
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.work_in_progress.HbsmsBeam.Move.Type
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.work_in_progress.VcPc.CpcTripleType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.search.work_in_progress.VcPcFast.CpcTripleType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.sem.ParamComparison
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.sem.ParamConstraintType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.sem.ParamType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.sem.ScoreType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.sem.StandardizedSemIm.Initialization
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.study.performance.Comparison.TableColumn
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.study.performance.Comparison2.TableColumn
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.Algorithm
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.DataType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.IndependenceTestType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.study.performance.ComparisonParameters.ResultType
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.util.MillisecondTimes.Type
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.cmu.tetrad.util.TextTable.Delimiter
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCCausalInference.OP
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.pitt.dbmi.algo.bayesian.constraint.inference.BCInference.OP
Returns an array containing the constants of this enum class, in the order they are declared.
values() - Static method in enum class edu.pitt.dbmi.algo.resampling.ResamplingEdgeEnsemble
Returns an array containing the constants of this enum class, in the order they are declared.
values(A) - Method in class edu.pitt.isp.sverchkov.data.AdTree
Returns the number of rows in the data set.
valuesToString() - Method in class edu.cmu.tetrad.simulation.PRAOerrors
valuesToString.
VAR - Enum constant in enum class edu.cmu.tetrad.sem.ParamType
Represents the error variance parameter in a structural equation modeling (SEM) model.
VAR_HIGH - Static variable in class edu.cmu.tetrad.util.Params
Constant VAR_HIGH="varHigh"
VAR_LOW - Static variable in class edu.cmu.tetrad.util.Params
Constant VAR_LOW="varLow"
varHat(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
varHat.
varHat(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
varHat.
varHat(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
varHat.
varHat(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
varHat.
Variable - Interface in edu.cmu.tetrad.data
Interface implemented by classes, instantiations of which are capable of serving as variables for columns in a DataSet.
VariableExpression - Class in edu.cmu.tetrad.calculator.expression
An Expression for a variable.
VariableExpression(String) - Constructor for class edu.cmu.tetrad.calculator.expression.VariableExpression
Constructor for VariableExpression.
variables() - Method in interface edu.pitt.isp.sverchkov.data.DataTable
variables.
variables() - Method in class edu.pitt.isp.sverchkov.data.DataTableImpl
variables.
variablesForIndices(List<Integer>, List<Node>) - Static method in class edu.cmu.tetrad.search.utils.ClusterSignificance
Converts a list of indices into a list of Nodes representing a cluster.
variablesForIndices2(Set<List<Integer>>, List<Node>) - Static method in class edu.cmu.tetrad.search.utils.ClusterSignificance
Converts a list of indices into a list of Nodes representing a cluster.
VariableSource - Interface in edu.cmu.tetrad.data
Inteface implemented by classes, instantiations of which are associated with lists of variables.
variance(double[]) - Static method in class edu.cmu.tetrad.util.StatUtils
variance.
variance(double[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
variance.
variance(long[]) - Static method in class edu.cmu.tetrad.util.StatUtils
variance.
variance(long[], int) - Static method in class edu.cmu.tetrad.util.StatUtils
variance.
Variance - Interface in edu.cmu.tetrad.stat
Feb 9, 2016 3:18:03 PM
VarianceVector - Class in edu.cmu.tetrad.stat
Feb 9, 2016 3:18:44 PM
VarianceVector(float[][]) - Constructor for class edu.cmu.tetrad.stat.VarianceVector
Constructor for VarianceVector.
VarianceVectorForkJoin - Class in edu.cmu.tetrad.stat
Feb 9, 2016 3:19:52 PM
VarianceVectorForkJoin(float[][], int) - Constructor for class edu.cmu.tetrad.stat.VarianceVectorForkJoin
Constructor for VarianceVectorForkJoin.
VarResult(DataSet, Graph) - Constructor for class edu.cmu.tetrad.search.utils.TsUtils.VarResult
Constructs a new result.
VcFas - Class in edu.cmu.tetrad.search.work_in_progress
Implements the "fast adjacency search" used in several causal algorithm in this package.
VcFas(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.work_in_progress.VcFas
Constructor for VcFas.
VcPc - Class in edu.cmu.tetrad.search.work_in_progress
Implements a convervative version of PC, in which the Markov condition is assumed but faithfulness is tested locally.
VcPc(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.work_in_progress.VcPc
Constructs a CPC algorithm that uses the given independence test as oracle.
VcPc.CpcTripleType - Enum Class in edu.cmu.tetrad.search.work_in_progress
An enum of triple types.
VcPcAlt - Class in edu.cmu.tetrad.search.work_in_progress
Implements a convervative version of PC, in which the Markov condition is assumed but faithfulness is tested locally.
VcPcAlt(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.work_in_progress.VcPcAlt
Constructs a CPC algorithm that uses the given independence test as oracle.
VcPcFast - Class in edu.cmu.tetrad.search.work_in_progress
Implements a convervative version of PC, in which the Markov condition is assumed but faithfulness is tested locally.
VcPcFast(IndependenceTest) - Constructor for class edu.cmu.tetrad.search.work_in_progress.VcPcFast
Constructs a CPC algorithm that uses the given independence test as oracle.
VcPcFast.CpcTripleType - Enum Class in edu.cmu.tetrad.search.work_in_progress
An enum of the types of triples that can be found in a graph.
vec(double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
vec.
vech(double[][]) - Static method in class edu.cmu.tetrad.util.MatrixUtils
vech.
vechToVecLeft(int) - Static method in class edu.cmu.tetrad.util.MatrixUtils
The matrix which, when postmultiplied by vech, return vec.
vecMax(DoubleMatrix1D) - Static method in class edu.pitt.csb.mgm.MixedUtils
vecMax.
Vector - Class in edu.cmu.tetrad.util
Vector wrapping matrix library.
Vector(double[]) - Constructor for class edu.cmu.tetrad.util.Vector
Constructs a new Vector object from an array of double values.
Vector(int) - Constructor for class edu.cmu.tetrad.util.Vector
Constructs a new Vector object with the specified size.
Vector(RealVector) - Constructor for class edu.cmu.tetrad.util.Vector
Creates a new Vector object from a RealVector object.
verbose - Variable in class edu.cmu.tetrad.search.utils.TetradTestDiscrete
Whether to print out verbose information.
VERBOSE - Static variable in class edu.cmu.tetrad.util.Params
Constant VERBOSE="verbose"
Version - Class in edu.cmu.tetrad.util
Represents the getModel Tetrad version.
Version(String) - Constructor for class edu.cmu.tetrad.util.Version
Parses string version specs into Versions.
VerticalDoubleDataBox - Class in edu.cmu.tetrad.data
Stores a 2D array of double data.
VerticalDoubleDataBox(double[][]) - Constructor for class edu.cmu.tetrad.data.VerticalDoubleDataBox
Constructs a new data box using the given 2D double data array as data.
VerticalDoubleDataBox(int, int) - Constructor for class edu.cmu.tetrad.data.VerticalDoubleDataBox
Constructs an 2D double array consisting entirely of missing values (Double.NaN).
VerticalDoubleDataBox(DataBox) - Constructor for class edu.cmu.tetrad.data.VerticalDoubleDataBox
Copies the data from the given data box into this one.
VerticalIntDataBox - Class in edu.cmu.tetrad.data
Stores a 2D array of int data.
VerticalIntDataBox(int[][]) - Constructor for class edu.cmu.tetrad.data.VerticalIntDataBox
Constructs a new data box using the given 2D int data array as data.
VerticalIntDataBox(int, int) - Constructor for class edu.cmu.tetrad.data.VerticalIntDataBox
Constructs an 2D int array consisting entirely of missing values (int.NaN).
VerticalIntDataBox(DataBox) - Constructor for class edu.cmu.tetrad.data.VerticalIntDataBox
Constructor for VerticalIntDataBox.
Vicinity - Class in edu.cmu.tetrad.simulation
This version of Vicinity finds nearby nodes by searching with an expanding cube Prior to Vicinity4, versions of Vicinity looked at the 3 axis independently instead of collectively.
Vicinity(List<Edge>, DataSet, int, int, int, int, int, int, double, double, double) - Constructor for class edu.cmu.tetrad.simulation.Vicinity
Constructor for Vicinity.
viewSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.ByteDataBox
viewSelection.
viewSelection(int[], int[]) - Method in interface edu.cmu.tetrad.data.DataBox
viewSelection.
viewSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.DoubleDataBox
viewSelection.
viewSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.FloatDataBox
viewSelection.
viewSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.IntDataBox
viewSelection.
viewSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.LongDataBox
viewSelection.
viewSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.MixedDataBox
viewSelection.
viewSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.ShortDataBox
viewSelection.
viewSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.VerticalDoubleDataBox
viewSelection.
viewSelection(int[], int[]) - Method in class edu.cmu.tetrad.data.VerticalIntDataBox
viewSelection.
visibleEdgeAdjustments1(Graph, Node, Node, int, GraphUtils.GraphType) - Static method in class edu.cmu.tetrad.graph.GraphUtils
Calculates visual-edge adjustments given graph G between two nodes x and y that are subsets of MB(X).
visibleEdgeAdjustments3(Graph, Node, Node, int, GraphUtils.GraphType) - Static method in class edu.cmu.tetrad.graph.GraphUtils
This method calculates visible-edge adjustments for a given graph, two nodes, a number of smallest sizes, and a graph type.

W

W_THRESHOLD - Static variable in class edu.cmu.tetrad.util.Params
Constant W_THRESHOLD="wThreshold"
Wall - Enum constant in enum class edu.cmu.tetrad.util.MillisecondTimes.Type
Wall time.
wallTimeMillis() - Static method in class edu.cmu.tetrad.util.MillisecondTimes
wallTimeMillis.
warning(String) - Method in class edu.cmu.tetrad.util.LogUtils
warning.
Washdown - Class in edu.cmu.tetrad.search.work_in_progress
Implements the Washdown algorithm,
Washdown(DataSet, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Washdown
Constructor.
Washdown(ICovarianceMatrix, double) - Constructor for class edu.cmu.tetrad.search.work_in_progress.Washdown
Constructor.
weakUnion() - Method in class edu.cmu.tetrad.search.utils.GraphoidAxioms
Checks is weak union holds, e.g., X _||_ Y U W | Z ==> X _||_ Y | Z U W
WHITESPACE - Enum constant in enum class edu.cmu.tetrad.calculator.parser.Token
Whitespace.
WHITESPACE - Static variable in class edu.cmu.tetrad.data.DelimiterType
Constant WHITESPACE
worsleyfriston - Enum constant in enum class edu.cmu.tetrad.search.utils.ResolveSepsets.Method
Worsley and Friston's method
worsleyfriston - Enum constant in enum class edu.cmu.tetrad.search.work_in_progress.ResolveSepsetsDci.Method
The wilkinson method.
wouldBeSatisfied(double) - Method in class edu.cmu.tetrad.sem.ParamConstraint
This method is for testing whether a value that might be assigned to a parameter would satisfy it.
writeCovMatrix(ICovarianceMatrix, PrintWriter, NumberFormat) - Static method in class edu.cmu.tetrad.data.DataWriter
Writes the lower triangle of a covariance matrix to file.
writeRectangularData(DataSet, Writer, char) - Static method in class edu.cmu.tetrad.data.DataWriter
Writes a dataset to file.

Z

zeros(int, int) - Static method in class edu.cmu.tetrad.util.MatrixUtils
zeros.
zhangMagFromPag(Graph) - Static method in class edu.cmu.tetrad.graph.GraphTransforms
Transforms a partial ancestral graph (PAG) into a maximal ancestral graph (MAG) using Zhang's 2008 Theorem 2.
ZhangShenBoundScore - Class in edu.cmu.tetrad.algcomparison.score
Wrapper for linear, Gaussian Extended BIC score (Chen and Chen).
ZhangShenBoundScore() - Constructor for class edu.cmu.tetrad.algcomparison.score.ZhangShenBoundScore
This class represents the constructor for the ZhangShenBoundScore class.
ZS_RISK_BOUND - Static variable in class edu.cmu.tetrad.util.Params
Constant ZS_RISK_BOUND="zSRiskBound"
ZsbScore - Class in edu.cmu.tetrad.search.score
Implements an unpublished score based on a risk bound due to Zhang and Shen.
ZsbScore(DataSet, boolean) - Constructor for class edu.cmu.tetrad.search.score.ZsbScore
Constructs the score using a covariance matrix.
ZsbScore(ICovarianceMatrix) - Constructor for class edu.cmu.tetrad.search.score.ZsbScore
Constructs the score using a covariance matrix.
zSum() - Method in class edu.cmu.tetrad.util.Matrix
zSum.
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