Uses of Interface
edu.cmu.tetrad.graph.Node
Packages that use Node
Package
Description
Contains classes for searching for (mostly structural) causal models given data.
Contains classes for various various sorts of scores for running score-based algorithms.
Contains classes for running conditional independence tests for various sorts of data.
Contains some utility classes for search algorithms.
Contains some classes that aren't ready for prime time.
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Uses of Node in edu.cmu.tetrad.algcomparison.score
Methods in edu.cmu.tetrad.algcomparison.score that return NodeModifier and TypeMethodDescriptionBdeuScore.getVariable(String name) CciScore.getVariable(String name) ConditionalGaussianBicScore.getVariable(String name) DegenerateGaussianBicScore.getVariable(String name) DiscreteBicScore.getVariable(String name) EbicScore.getVariable(String name) FisherZScore.getVariable(String name) GicScores.getVariable(String name) MagSemBicScore.getVariable(String name) MSeparationScore.getVariable(String name) MVPBicScore.getVariable(String name) PoissonPriorScore.getVariable(String name) PositiveCorrScore.getVariable(String name) ScoreWrapper.getVariable(String name) Returns the variable with the given name.SemBicScore.getVariable(String name) SemBicScoreDeterministic.getVariable(String name) ZhangShenBoundScore.getVariable(String name) -
Uses of Node in edu.cmu.tetrad.algcomparison.statistic
Methods in edu.cmu.tetrad.algcomparison.statistic with parameters of type NodeModifier and TypeMethodDescriptionbooleanNumDirectedEdgeNoMeasureAncestors.existsDirectedPathFromTo(Graph graph, Node node1, Node node2) -
Uses of Node in edu.cmu.tetrad.bayes
Methods in edu.cmu.tetrad.bayes that return NodeModifier and TypeMethodDescriptionstatic Node[]GraphTools.getMaximumCardinalityOrdering(Graph graph) Perform Tarjan and Yannakakis (1984) maximum cardinality search (MCS) to get the maximum cardinality ordering.BayesIm.getNode(int nodeIndex) Returns the name of the given node.Returns the name of the given node.BayesPm.getNode(int index) Returns the node at the given index.Returns the node by the given name.DirichletBayesIm.getNode(int nodeIndex) Evidence.getNode(int nodeIndex) MlBayesIm.getNode(int nodeIndex) MlBayesImObs.getNode(int nodeIndex) UpdatedBayesIm.getNode(int nodeIndex) BayesPm.getVariable(Node node) Returns the variable for the given node.BayesProperties.getVariable(String targetName) Methods in edu.cmu.tetrad.bayes that return types with arguments of type NodeModifier and TypeMethodDescriptionGraphTools.getCliques(Node[] ordering, Graph graph) Get cliques in a decomposable graph.GraphTools.getCliques(Node[] ordering, Graph graph) Get cliques in a decomposable graph.GraphTools.getCliqueTree(Node[] ordering, Map<Node, Set<Node>> cliques, Map<Node, Set<Node>> separators) GraphTools.getCliqueTree(Node[] ordering, Map<Node, Set<Node>> cliques, Map<Node, Set<Node>> separators) BayesIm.getMeasuredNodes()Returns the list of measured variables.BayesPm.getMeasuredNodes()Returns the measured nodes.DirichletBayesIm.getMeasuredNodes()MlBayesIm.getMeasuredNodes()MlBayesImObs.getMeasuredNodes()UpdatedBayesIm.getMeasuredNodes()JunctionTreeAlgorithm.getNodes()Calculate separator sets in clique tree.Calculate separator sets in clique tree.BayesIm.getVariables()Returns the list of variables.BayesImProbs.getVariables()BayesPm.getVariables()CellTableProbs.getVariables()DataSetProbs.getVariables()DirichletBayesIm.getVariables()DirichletDataSetProbs.getVariables()IntAveDataSetProbs.getVariables()MlBayesIm.getVariables()MlBayesImObs.getVariables()StoredCellProbs.getVariables()StoredCellProbsObs.getVariables()UpdatedBayesIm.getVariables()Evidence.getVariablesInEvidence()Methods in edu.cmu.tetrad.bayes with parameters of type NodeModifier and TypeMethodDescriptionstatic voidApply Tarjan and Yannakakis (1984) fill in algorithm for graph triangulation.BayesPm.getCategory(Node node, int index) Returns the index'th value for the given node.Evidence.getCategory(Node node, int j) intBayesPm.getCategoryIndex(Node node, String category) Returns the index of the given category for the given node.GraphTools.getCliques(Node[] ordering, Graph graph) Get cliques in a decomposable graph.GraphTools.getCliqueTree(Node[] ordering, Map<Node, Set<Node>> cliques, Map<Node, Set<Node>> separators) intBayesIm.getNodeIndex(Node node) Returns the index of the given node.intDirichletBayesIm.getNodeIndex(Node node) intMlBayesIm.getNodeIndex(Node node) intMlBayesImObs.getNodeIndex(Node node) intUpdatedBayesIm.getNodeIndex(Node node) intBayesPm.getNumCategories(Node node) Returns the number of values for the given node.double[][]BdeMetricCache.getObservedCounts(Node node, BayesPm bayesPm, BayesIm bayesIm) This method is used in testing and debugging and not in the BDe metric calculations.intBdeMetricCache.getScoreCount(Node node, Set<Node> parents) This is just for testing the operation of the inner class and the map from nodes and parent sets to scores.Calculate separator sets in clique tree.BayesPm.getVariable(Node node) Returns the variable for the given node.doubleComputes the BDe score, using the logarithm of the gamma function, relative to the data, of the factor determined by a node and its parents.voidBayesPm.setCategories(Node node, List<String> categories) Sets the number of values for the given node to the given number.voidBayesPm.setNumCategories(Node node, int numCategories) Sets the number of values for the given node to the given number.Method parameters in edu.cmu.tetrad.bayes with type arguments of type NodeModifier and TypeMethodDescriptionstatic StoredCellProbsStoredCellProbs.createRandomCellTable(List<Node> variables) GraphTools.getCliqueTree(Node[] ordering, Map<Node, Set<Node>> cliques, Map<Node, Set<Node>> separators) GraphTools.getCliqueTree(Node[] ordering, Map<Node, Set<Node>> cliques, Map<Node, Set<Node>> separators) intBdeMetricCache.getScoreCount(Node node, Set<Node> parents) This is just for testing the operation of the inner class and the map from nodes and parent sets to scores.Calculate separator sets in clique tree.Calculate separator sets in clique tree.doubleComputes the BDe score, using the logarithm of the gamma function, relative to the data, of the factor determined by a node and its parents.Constructor parameters in edu.cmu.tetrad.bayes with type arguments of type Node -
Uses of Node in edu.cmu.tetrad.classify
Methods in edu.cmu.tetrad.classify that return types with arguments of type NodeModifier and TypeMethodDescriptionClassifierBayesUpdaterDiscrete.getBayesImVars()Returns the variables of the BayesIM. -
Uses of Node in edu.cmu.tetrad.data
Subinterfaces of Node in edu.cmu.tetrad.dataModifier and TypeInterfaceDescriptioninterfaceInterface implemented by classes, instantiations of which are capable of serving as variables for columns in a DataSet.Classes in edu.cmu.tetrad.data that implement NodeModifier and TypeClassDescriptionclassBase class for variable specifications for DataSet.final classRepresents a real-valued variable.final classRepresents a discrete variable as a range of integer-valued categories 0, 1, ..., m - 1, where m is the number of categories for the variable.Methods in edu.cmu.tetrad.data that return NodeModifier and TypeMethodDescriptionHistogram.getTargetNode()BoxDataSet.getVariable(int col) BoxDataSet.getVariable(String varName) CorrelationMatrixOnTheFly.getVariable(String name) CovarianceMatrix.getVariable(String name) CovarianceMatrixOnTheFly.getVariable(String name) DataModel.getVariable(String name) DataModelList.getVariable(String name) DataSet.getVariable(int column) DataSet.getVariable(String name) ICovarianceMatrix.getVariable(String name) IndependenceFacts.getVariable(String name) NumberObjectDataSet.getVariable(int col) NumberObjectDataSet.getVariable(String varName) TimeSeriesData.getVariable(String name) abstract NodeMethods in edu.cmu.tetrad.data that return types with arguments of type NodeModifier and TypeMethodDescriptionDataUtils.createContinuousVariables(String[] varNames) DataTransforms.getConstantColumns(DataSet dataSet) DataUtils.getExampleNonsingular(ICovarianceMatrix covarianceMatrix, int depth) NumberObjectDataSet.getSelectedVariables()BoxDataSet.getVariables()CorrelationMatrixOnTheFly.getVariables()CovarianceMatrix.getVariables()CovarianceMatrixOnTheFly.getVariables()DataModelList.getVariables()DataSet.getVariables()ICovarianceMatrix.getVariables()IndependenceFacts.getVariables()NumberObjectDataSet.getVariables()TimeSeriesData.getVariables()VariableSource.getVariables()Returns the list of variables associated with this object.Methods in edu.cmu.tetrad.data with parameters of type NodeModifier and TypeMethodDescriptionvoidBoxDataSet.addVariable(int index, Node variable) Adds the given variable to the dataset, increasing the number of columns by one, moving columns i >=indexto column i + 1, and inserting a column of missing values at column i.voidBoxDataSet.addVariable(Node variable) Adds the given variable to the data set, increasing the number of columns by one, moving columns i >=indexto column i + 1, and inserting a column of missing values at column i.voidDataSet.addVariable(int index, Node variable) Adds the given variable at the given index.voidDataSet.addVariable(Node variable) Adds the given variable to the data set.voidMixedDataBox.addVariable(Node variable) voidNumberObjectDataSet.addVariable(int index, Node variable) Adds the given variable to the dataset, increasing the number of columns by one, moving columns i >=indexto column i + 1, and inserting a column of missing values at column i.voidNumberObjectDataSet.addVariable(Node variable) Adds the given variable to the data set, increasing the number of columns by one, moving columns i >=indexto column i + 1, and inserting a column of missing values at column i.voidBoxDataSet.changeVariable(Node from, Node to) Changes the variable for the given column fromfromtoto.voidDataSet.changeVariable(Node from, Node to) Changes the variable for the given column fromfromtoto.voidNumberObjectDataSet.changeVariable(Node from, Node to) Changes the variable for the given column fromfromtoto.static voidDataTransforms.copyColumn(Node node, DataSet source, DataSet dest) voidDiscretizer.equalCounts(Node node, int numCategories) Sets the given node to discretized using evenly distributed values using the given number of categories.voidDiscretizer.equalIntervals(Node node, int numCategories) Sets the given node to discretized using evenly spaced intervals using the given number of categories.intintintbooleanIndependenceFacts.isIndependent(Node x, Node y, Node... z) booleanIndependenceFacts.isIndependent(Node x, Node y, Set<Node> z) intKnowledge.isInWhichTier(Node node) Returns the index of the tier of node if it's in a tier, otherwise -1.booleanBoxDataSet.isSelected(Node variable) final booleanCorrelationMatrixOnTheFly.isSelected(Node variable) final booleanCovarianceMatrix.isSelected(Node variable) final booleanCovarianceMatrixOnTheFly.isSelected(Node variable) booleanDataSet.isSelected(Node variable) booleanICovarianceMatrix.isSelected(Node variable) booleanNumberObjectDataSet.isSelected(Node variable) voidBoxDataSet.removeColumn(Node variable) Removes the columns for the given variable from the dataset, reducing the number of columns by one.voidDataSet.removeColumn(Node variable) Removes the given variable, along with all of its data.voidNumberObjectDataSet.removeColumn(Node variable) Removes the columns for the given variable from the dataset, reducing the number of columns by one.final voidfinal voidfinal voidvoidvoidBoxDataSet.setSelected(Node variable, boolean selected) Marks the given column as selected if 'selected' is true or deselected if 'selected' is false.voidDataSet.setSelected(Node variable, boolean selected) Marks the given column as selected if 'selected' is true or deselected if 'selected' is false.voidNumberObjectDataSet.setSelected(Node variable, boolean selected) Marks the given column as selected if 'selected' is true or deselected if 'selected' is false.static Matrixstatic Matrixstatic Matrixstatic MatrixMethod parameters in edu.cmu.tetrad.data with type arguments of type NodeModifier and TypeMethodDescriptionbooleanIndependenceFacts.isIndependent(Node x, Node y, Set<Node> z) voidvoidCorrelationMatrixOnTheFly.setVariables(List<Node> variables) voidCovarianceMatrix.setVariables(List<Node> variables) voidCovarianceMatrixOnTheFly.setVariables(List<Node> variables) voidICovarianceMatrix.setVariables(List<Node> variables) static Matrixstatic Matrixstatic Matrixstatic Matrixstatic Matrixstatic MatrixBoxDataSet.subsetColumns(List<Node> vars) Creates and returns a dataset consisting of those variables in the list vars.DataSet.subsetColumns(List<Node> vars) Creates and returns a dataset consisting of those variables in the list vars.NumberObjectDataSet.subsetColumns(List<Node> vars) Creates and returns a dataset consisting of those variables in the list vars.Constructor parameters in edu.cmu.tetrad.data with type arguments of type NodeModifierConstructorDescriptionBoxDataSet(DataBox dataBox, List<Node> variables) CorrelationMatrix(List<Node> variables, Matrix matrix, int sampleSize) Constructs a correlation matrix data set using the given information.CovarianceMatrix(List<Node> variables, double[][] matrix, int sampleSize) CovarianceMatrix(List<Node> variables, Matrix matrix, int sampleSize) Protected constructor to construct a new covariance matrix using the supplied continuous variables and the the given symmetric, positive definite matrix and sample size.Discretizer(DataSet dataSet, Map<Node, DiscretizationSpec> specs) MixedDataBox(List<Node> variables, int numRows) The variables here are used only to determine which columns are discrete and which are continuous; bounds checking is not done.MixedDataBox(List<Node> variables, int numRows, double[][] continuousData, int[][] discreteData) This constructor allows other data readers to populate the fields directly.NumberObjectDataSet(Number[][] data, List<Node> variables) -
Uses of Node in edu.cmu.tetrad.graph
Classes in edu.cmu.tetrad.graph that implement NodeModifier and TypeClassDescriptionclassImplements a basic node in a graph--that is, a node that is not itself a variable.Methods in edu.cmu.tetrad.graph that return NodeModifier and TypeMethodDescriptionstatic NodeGraphUtils.getAssociatedNode(Node errorNode, Graph graph) static NodeEdges.getDirectedEdgeHead(Edge edge) For a directed edge, returns the node adjacent to the arrow endpoint.static NodeEdges.getDirectedEdgeTail(Edge edge) For a directed edge, returns the node adjacent to the null endpoint.final NodeEdge.getDistalNode(Node node) Traverses the edge in an undirected fashion--given one node along the edge, returns the node at the opposite end of the edge.SemGraph.getErrorNode(Node node) SemGraph.getExogenous(Node node) NodePair.getFirst()final NodeEdge.getNode1()final NodeEdge.getNode2()NodePair.getSecond()SemGraph.getVarNode(Node node) IndependenceFact.getX()Triple.getX()IndependenceFact.getY()Triple.getY()Triple.getZ()Creates a new node of the same type as this one with the given name.static Nodestatic NodeEdges.traverseDirected(Node node, Edge edge) For A -> B, given A, returns B; otherwise returns null.static NodeEdges.traverseReverseDirected(Node node, Edge edge) For A -> B, given B, returns A; otherwise returns null.static NodeEdges.traverseSemiDirected(Node node, Edge edge) For A --* B or A o-* B, given A, returns B.static NodeGraphUtils.traverseSemiDirected(Node node, Edge edge) Methods in edu.cmu.tetrad.graph that return types with arguments of type NodeModifier and TypeMethodDescriptionPaths.allDirectedPathsFromTo(Node node1, Node node2, int maxLength) Paths.allPathsFromTo(Node node1, Node node2, int maxLength) Constructs a list of nodes from the givennodeslist at the given indices in that list.Paths.connectedComponents()Paths.directedPathsFromTo(Node node1, Node node2, int maxLength) Dag.getAdjacentNodes(Node node) EdgeListGraph.getAdjacentNodes(Node node) Graph.getAdjacentNodes(Node node) LagGraph.getAdjacentNodes(Node node) SemGraph.getAdjacentNodes(Node node) TimeLagGraph.getAdjacentNodes(Node node) Paths.getAncestorMap()Return a map from each node to its ancestors.Paths.getAncestorMap()Return a map from each node to its ancestors.Paths.getAncestors(List<Node> nodes) Dag.getChildren(Node node) EdgeListGraph.getChildren(Node node) Graph.getChildren(Node node) LagGraph.getChildren(Node node) SemGraph.getChildren(Node node) TimeLagGraph.getChildren(Node node) Paths.getDescendants(List<Node> nodes) SemGraph.getFullTierOrdering()Paths.getInducingPath(Node x, Node y) TimeLagGraph.getLag0Nodes()Paths.getMConnectedVars(Node y, Set<Node> z) Dag.getNodes()EdgeListGraph.getNodes()Graph.getNodes()LagGraph.getNodes()SemGraph.getNodes()TimeLagGraph.getNodes()Dag.getNodesInTo(Node node, Endpoint n) EdgeListGraph.getNodesInTo(Node node, Endpoint endpoint) Nodes adjacent to the given node with the given proximal endpoint.Graph.getNodesInTo(Node node, Endpoint n) Nodes adjacent to the given node with the given proximal endpoint.LagGraph.getNodesInTo(Node node, Endpoint n) SemGraph.getNodesInTo(Node node, Endpoint endpoint) TimeLagGraph.getNodesInTo(Node node, Endpoint endpoint) Dag.getNodesOutTo(Node node, Endpoint n) EdgeListGraph.getNodesOutTo(Node node, Endpoint endpoint) Nodes adjacent to the given node with the given distal endpoint.Graph.getNodesOutTo(Node node, Endpoint n) Nodes adjacent to the given node with the given distal endpoint.LagGraph.getNodesOutTo(Node node, Endpoint n) SemGraph.getNodesOutTo(Node node, Endpoint n) TimeLagGraph.getNodesOutTo(Node node, Endpoint endpoint) Dag.getParents(Node node) EdgeListGraph.getParents(Node node) Graph.getParents(Node node) LagGraph.getParents(Node node) SemGraph.getParents(Node node) TimeLagGraph.getParents(Node node) Paths.getValidOrder(List<Node> initialOrder, boolean forward) Returns a valid causal order for either a DAG or a CPDAG.IndependenceFact.getZ()GraphUtils.markovBlanket(Node x, Graph G) Returns a Markov blanket of a node for a DAG, CPDAG, MAG, or PAG.Paths.maxCliques()GraphUtils.maximalCliques(Graph graph, List<Node> nodes) Paths.possibleMsep(Node x, Node y, int maxPathLength) GraphUtils.replaceNodes(List<Node> originalNodes, Graph graph) Converts the given list of nodes,originalNodes, to use the replacement nodes for them by the same name in the givengraph.GraphUtils.replaceNodes(List<Node> originalNodes, List<Node> newNodes) Converts the given list of nodes,originalNodes, to use the new variables (with the same names as the old).Paths.semidirectedPathsFromTo(Node node1, Node node2, int maxLength) Paths.treksIncludingBidirected(Node node1, Node node2) Methods in edu.cmu.tetrad.graph with parameters of type NodeModifier and TypeMethodDescriptionvoidDag.addAmbiguousTriple(Node x, Node y, Node z) voidEdgeListGraph.addAmbiguousTriple(Node x, Node y, Node z) voidGraph.addAmbiguousTriple(Node x, Node y, Node z) voidLagGraph.addAmbiguousTriple(Node x, Node y, Node z) voidSemGraph.addAmbiguousTriple(Node x, Node y, Node z) voidTimeLagGraph.addAmbiguousTriple(Node x, Node y, Node z) voidUnderlines.addAmbiguousTriple(Node x, Node y, Node z) booleanDag.addBidirectedEdge(Node node1, Node node2) booleanEdgeListGraph.addBidirectedEdge(Node node1, Node node2) Adds a bidirected edge to the graph from node A to node B.booleanGraph.addBidirectedEdge(Node node1, Node node2) Adds a bidirected edges <-> to the graph.booleanLagGraph.addBidirectedEdge(Node node1, Node node2) booleanSemGraph.addBidirectedEdge(Node nodeA, Node nodeB) booleanTimeLagGraph.addBidirectedEdge(Node node1, Node node2) booleanDag.addDirectedEdge(Node node1, Node node2) booleanEdgeListGraph.addDirectedEdge(Node node1, Node node2) Adds a directed edge to the graph from node A to node B.booleanGraph.addDirectedEdge(Node node1, Node node2) Adds a directed edge --> to the graph.booleanLagGraph.addDirectedEdge(Node node1, Node node2) booleanSemGraph.addDirectedEdge(Node nodeA, Node nodeB) booleanTimeLagGraph.addDirectedEdge(Node node1, Node node2) voidDag.addDottedUnderlineTriple(Node x, Node y, Node z) voidEdgeListGraph.addDottedUnderlineTriple(Node x, Node y, Node z) voidGraph.addDottedUnderlineTriple(Node x, Node y, Node z) voidLagGraph.addDottedUnderlineTriple(Node x, Node y, Node z) voidSemGraph.addDottedUnderlineTriple(Node x, Node y, Node z) voidTimeLagGraph.addDottedUnderlineTriple(Node x, Node y, Node z) voidUnderlines.addDottedUnderlineTriple(Node x, Node y, Node z) booleanbooleanAdds a node to the graph.booleanAdds a node to the graph.booleanbooleanbooleanNodes may be added into the getModel time step only.booleanDag.addNondirectedEdge(Node node1, Node node2) booleanEdgeListGraph.addNondirectedEdge(Node node1, Node node2) Adds a nondirected edge to the graph from node A to node B.booleanGraph.addNondirectedEdge(Node node1, Node node2) Adds a nondirected edges o-o to the graph.booleanLagGraph.addNondirectedEdge(Node node1, Node node2) booleanSemGraph.addNondirectedEdge(Node nodeA, Node nodeB) booleanTimeLagGraph.addNondirectedEdge(Node node1, Node node2) booleanDag.addPartiallyOrientedEdge(Node node1, Node node2) booleanEdgeListGraph.addPartiallyOrientedEdge(Node node1, Node node2) Adds a partially oriented edge to the graph from node A to node B.booleanGraph.addPartiallyOrientedEdge(Node node1, Node node2) Adds a partially oriented edge o-> to the graph.booleanLagGraph.addPartiallyOrientedEdge(Node node1, Node node2) booleanSemGraph.addPartiallyOrientedEdge(Node nodeA, Node nodeB) booleanTimeLagGraph.addPartiallyOrientedEdge(Node node1, Node node2) voidDag.addUnderlineTriple(Node x, Node y, Node z) voidEdgeListGraph.addUnderlineTriple(Node x, Node y, Node z) voidGraph.addUnderlineTriple(Node x, Node y, Node z) voidLagGraph.addUnderlineTriple(Node x, Node y, Node z) voidSemGraph.addUnderlineTriple(Node x, Node y, Node z) voidTimeLagGraph.addUnderlineTriple(Node x, Node y, Node z) voidUnderlines.addUnderlineTriple(Node x, Node y, Node z) booleanDag.addUndirectedEdge(Node node1, Node node2) booleanEdgeListGraph.addUndirectedEdge(Node node1, Node node2) Adds an undirected edge to the graph from node A to node B.booleanGraph.addUndirectedEdge(Node node1, Node node2) Adds an undirected edge --- to the graph.booleanLagGraph.addUndirectedEdge(Node node1, Node node2) booleanSemGraph.addUndirectedEdge(Node nodeA, Node nodeB) booleanTimeLagGraph.addUndirectedEdge(Node node1, Node node2) Paths.allDirectedPathsFromTo(Node node1, Node node2, int maxLength) Paths.allPathsFromTo(Node node1, Node node2, int maxLength) static EdgeEdges.bidirectedEdge(Node nodeA, Node nodeB) Constructs a new bidirected edge from nodeA to nodeB (<->).default intReturns the hashcode for this node.booleanDag.containsNode(Node node) booleanEdgeListGraph.containsNode(Node node) Determines whether the graph contains a particular node.booleanGraph.containsNode(Node node) Determines whether this graph contains the given node.booleanLagGraph.containsNode(Node node) booleanSemGraph.containsNode(Node node) booleanTimeLagGraph.containsNode(Node node) booleanPaths.definiteNonDescendent(Node node1, Node node2) added by ekorber, 2004/06/12static EdgeEdges.directedEdge(Node nodeA, Node nodeB) Constructs a new directed edge from nodeA to nodeB (-->).Paths.directedPathsFromTo(Node node1, Node node2, int maxLength) booleanPaths.existsDirectedPathFromTo(Node node1, Node node2) booleanPaths.existsDirectedPathFromTo(Node node1, Node node2, int depth) booleanPaths.existsInducingPath(Node x, Node y) Determines whether an inducing path exists between node1 and node2, given a set O of observed nodes and a set sem of conditioned nodes.booleanPaths.existsInducingPathVisit(Node a, Node b, Node x, Node y, LinkedList<Node> path) booleanPaths.existsSemiDirectedPath(Node from, Node to) booleanPaths.existsSemiDirectedPath(Node node1, Set<Node> nodes) booleanPaths.existsTrek(Node node1, Node node2) Determines whether a trek exists between two nodes in the graph.Dag.getAdjacentNodes(Node node) EdgeListGraph.getAdjacentNodes(Node node) Graph.getAdjacentNodes(Node node) LagGraph.getAdjacentNodes(Node node) SemGraph.getAdjacentNodes(Node node) TimeLagGraph.getAdjacentNodes(Node node) GraphUtils.getAmbiguousTriplesFromGraph(Node node, Graph graph) static NodeGraphUtils.getAssociatedNode(Node errorNode, Graph graph) Dag.getChildren(Node node) EdgeListGraph.getChildren(Node node) Graph.getChildren(Node node) LagGraph.getChildren(Node node) SemGraph.getChildren(Node node) TimeLagGraph.getChildren(Node node) GraphSaveLoadUtils.getCollidersFromGraph(Node node, Graph graph) intintintintintintDag.getDirectedEdge(Node node1, Node node2) EdgeListGraph.getDirectedEdge(Node node1, Node node2) Graph.getDirectedEdge(Node node1, Node node2) LagGraph.getDirectedEdge(Node node1, Node node2) SemGraph.getDirectedEdge(Node node1, Node node2) TimeLagGraph.getDirectedEdge(Node node1, Node node2) final EndpointEdge.getDistalEndpoint(Node node) final NodeEdge.getDistalNode(Node node) Traverses the edge in an undirected fashion--given one node along the edge, returns the node at the opposite end of the edge.GraphUtils.getDottedUnderlinedTriplesFromGraph(Node node, Graph graph) Dag.getEndpoint(Node node1, Node node2) EdgeListGraph.getEndpoint(Node node1, Node node2) Graph.getEndpoint(Node node1, Node node2) LagGraph.getEndpoint(Node node1, Node node2) SemGraph.getEndpoint(Node node1, Node node2) TimeLagGraph.getEndpoint(Node node1, Node node2) SemGraph.getErrorNode(Node node) SemGraph.getExogenous(Node node) intDag.getIndegree(Node node) intEdgeListGraph.getIndegree(Node node) intGraph.getIndegree(Node node) intLagGraph.getIndegree(Node node) intSemGraph.getIndegree(Node node) intTimeLagGraph.getIndegree(Node node) Paths.getInducingPath(Node x, Node y) Paths.getMConnectedVars(Node y, Set<Node> z) Dag.getNodesInTo(Node node, Endpoint n) EdgeListGraph.getNodesInTo(Node node, Endpoint endpoint) Nodes adjacent to the given node with the given proximal endpoint.Graph.getNodesInTo(Node node, Endpoint n) Nodes adjacent to the given node with the given proximal endpoint.LagGraph.getNodesInTo(Node node, Endpoint n) SemGraph.getNodesInTo(Node node, Endpoint endpoint) TimeLagGraph.getNodesInTo(Node node, Endpoint endpoint) Dag.getNodesOutTo(Node node, Endpoint n) EdgeListGraph.getNodesOutTo(Node node, Endpoint endpoint) Nodes adjacent to the given node with the given distal endpoint.Graph.getNodesOutTo(Node node, Endpoint n) Nodes adjacent to the given node with the given distal endpoint.LagGraph.getNodesOutTo(Node node, Endpoint n) SemGraph.getNodesOutTo(Node node, Endpoint n) TimeLagGraph.getNodesOutTo(Node node, Endpoint endpoint) intDag.getNumEdges(Node node) intEdgeListGraph.getNumEdges(Node node) intGraph.getNumEdges(Node node) intLagGraph.getNumEdges(Node node) intSemGraph.getNumEdges(Node node) intTimeLagGraph.getNumEdges(Node node) intDag.getOutdegree(Node node) intEdgeListGraph.getOutdegree(Node node) intGraph.getOutdegree(Node node) intLagGraph.getOutdegree(Node node) intSemGraph.getOutdegree(Node node) intTimeLagGraph.getOutdegree(Node node) Dag.getParents(Node node) EdgeListGraph.getParents(Node node) Graph.getParents(Node node) LagGraph.getParents(Node node) SemGraph.getParents(Node node) TimeLagGraph.getParents(Node node) final EndpointEdge.getProximalEndpoint(Node node) EdgeListGraph.getTriplesLists(Node node) TripleClassifier.getTriplesLists(Node node) Underlines.getTriplesLists(Node node) GraphUtils.getUnderlinedTriplesFromGraph(Node node, Graph graph) SemGraph.getVarNode(Node node) booleanDag.isAdjacentTo(Node node1, Node node2) booleanEdgeListGraph.isAdjacentTo(Node node1, Node node2) Determines whether some edge or other exists between two nodes.booleanGraph.isAdjacentTo(Node node1, Node node2) booleanLagGraph.isAdjacentTo(Node node1, Node node2) booleanSemGraph.isAdjacentTo(Node nodeX, Node nodeY) booleanTimeLagGraph.isAdjacentTo(Node node1, Node node2) booleanDag.isAmbiguousTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanEdgeListGraph.isAmbiguousTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanGraph.isAmbiguousTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanLagGraph.isAmbiguousTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanSemGraph.isAmbiguousTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanTimeLagGraph.isAmbiguousTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanUnderlines.isAmbiguousTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanLagGraph.isAncestorOf(Node node1, Node node2) booleanPaths.isAncestorOf(Node node1, Node node2) Determines whether one node is an ancestor of another.booleanbooleanDetermines whether one node is a child of another.booleanbooleanbooleanbooleanbooleanDag.isDefCollider(Node node1, Node node2, Node node3) booleanEdgeListGraph.isDefCollider(Node node1, Node node2, Node node3) booleanGraph.isDefCollider(Node node1, Node node2, Node node3) Added by ekorber, 2004/6/9.booleanLagGraph.isDefCollider(Node node1, Node node2, Node node3) booleanSemGraph.isDefCollider(Node node1, Node node2, Node node3) booleanTimeLagGraph.isDefCollider(Node node1, Node node2, Node node3) booleanDag.isDefNoncollider(Node node1, Node node2, Node node3) booleanEdgeListGraph.isDefNoncollider(Node node1, Node node2, Node node3) IllegalArgument exception raised (by isDirectedFromTo(getEndpoint) or by getEdge) if there are multiple edges between any of the node pairs.booleanGraph.isDefNoncollider(Node node1, Node node2, Node node3) Added by ekorber, 2004/6/9.booleanLagGraph.isDefNoncollider(Node node1, Node node2, Node node3) booleanSemGraph.isDefNoncollider(Node node1, Node node2, Node node3) booleanTimeLagGraph.isDefNoncollider(Node node1, Node node2, Node node3) booleanPaths.isDescendentOf(Node node1, Node node2) Determines whether one node is a descendent of another.booleanPaths.isDirectedFromTo(Node node1, Node node2) booleanDag.isExogenous(Node node) booleanEdgeListGraph.isExogenous(Node node) Determines whether a node in a graph is exogenous.booleanGraph.isExogenous(Node node) booleanLagGraph.isExogenous(Node node) booleanSemGraph.isExogenous(Node node) booleanTimeLagGraph.isExogenous(Node node) booleanPaths.isMConnectedTo(Node x, Node y, Set<Node> z) Detemrmines whether x and y are d-connected given z.booleanDetemrmines whether x and y are d-connected given z.booleanEdgeListGraph.isMSeparatedFrom(Node x, Node y, Set<Node> z) Determines whether x and y are d-separated given z.booleanPaths.isMSeparatedFrom(Node node1, Node node2, Set<Node> z) Determines whether one n ode is d-separated from another.booleanDag.isParameterizable(Node node) booleanEdgeListGraph.isParameterizable(Node node) booleanGraph.isParameterizable(Node node) booleanLagGraph.isParameterizable(Node node) booleanSemGraph.isParameterizable(Node node) booleanTimeLagGraph.isParameterizable(Node node) booleanDag.isParentOf(Node node1, Node node2) booleanEdgeListGraph.isParentOf(Node node1, Node node2) Determines whether one node is a parent of another.booleanGraph.isParentOf(Node node1, Node node2) Determines whether node1 is a parent of node2.booleanLagGraph.isParentOf(Node node1, Node node2) booleanSemGraph.isParentOf(Node node1, Node node2) booleanTimeLagGraph.isParentOf(Node node1, Node node2) booleanCheck to see if a set of variables Z satisfies the back-door criterion relative to node x and node y.booleanDag.isUnderlineTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanEdgeListGraph.isUnderlineTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanGraph.isUnderlineTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanLagGraph.isUnderlineTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanSemGraph.isUnderlineTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanTimeLagGraph.isUnderlineTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanUnderlines.isUnderlineTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanPaths.isUndirectedFromTo(Node node1, Node node2) GraphUtils.markovBlanket(Node x, Graph G) Returns a Markov blanket of a node for a DAG, CPDAG, MAG, or PAG.static GraphGraphUtils.markovBlanketSubgraph(Node target, Graph graph) Calculates the subgraph over the Markov blanket of a target node in a given DAG, CPDAG, MAG, or PAG.static EdgeEdges.nondirectedEdge(Node nodeA, Node nodeB) Constructs a new nondirected edge from nodeA to nodeB (o-o).static EdgeEdges.partiallyOrientedEdge(Node nodeA, Node nodeB) Constructs a new partially oriented edge from nodeA to nodeB (o->).static StringGraphUtils.pathString(Graph graph, Node... x) static StringTriple.pathString(Graph graph, Node x, Node y, Node z) booleanEdge.pointsTowards(Node node) booleanPaths.possibleAncestor(Node node1, Node node2) Paths.possibleMsep(Node x, Node y, int maxPathLength) voidDag.removeAmbiguousTriple(Node x, Node y, Node z) voidEdgeListGraph.removeAmbiguousTriple(Node x, Node y, Node z) voidGraph.removeAmbiguousTriple(Node x, Node y, Node z) voidLagGraph.removeAmbiguousTriple(Node x, Node y, Node z) voidSemGraph.removeAmbiguousTriple(Node x, Node y, Node z) voidTimeLagGraph.removeAmbiguousTriple(Node x, Node y, Node z) voidUnderlines.removeAmbiguousTriple(Node x, Node y, Node z) voidDag.removeDottedUnderlineTriple(Node x, Node y, Node z) voidEdgeListGraph.removeDottedUnderlineTriple(Node x, Node y, Node z) voidGraph.removeDottedUnderlineTriple(Node x, Node y, Node z) voidLagGraph.removeDottedUnderlineTriple(Node x, Node y, Node z) voidSemGraph.removeDottedUnderlineTriple(Node x, Node y, Node z) voidTimeLagGraph.removeDottedUnderlineTriple(Node x, Node y, Node z) voidUnderlines.removeDottedUnderlineTriple(Node x, Node y, Node z) booleanDag.removeEdge(Node node1, Node node2) booleanEdgeListGraph.removeEdge(Node node1, Node node2) Removes the edge connecting the two given nodes.booleanGraph.removeEdge(Node node1, Node node2) Removes the edge connecting the two given nodes, provided there is exactly one such edge.booleanLagGraph.removeEdge(Node node1, Node node2) booleanSemGraph.removeEdge(Node node1, Node node2) booleanTimeLagGraph.removeEdge(Node node1, Node node2) booleanDag.removeEdges(Node node1, Node node2) booleanEdgeListGraph.removeEdges(Node node1, Node node2) Removes all edges connecting node A to node B.booleanGraph.removeEdges(Node node1, Node node2) Removes all edges connecting node A to node B.booleanLagGraph.removeEdges(Node node1, Node node2) booleanSemGraph.removeEdges(Node node1, Node node2) booleanTimeLagGraph.removeEdges(Node node1, Node node2) booleanDag.removeNode(Node node) booleanEdgeListGraph.removeNode(Node node) Removes a node from the graph.booleanGraph.removeNode(Node node) Removes a node from the graph.booleanLagGraph.removeNode(Node node) booleanSemGraph.removeNode(Node node) booleanTimeLagGraph.removeNode(Node node) voidDag.removeUnderlineTriple(Node x, Node y, Node z) voidEdgeListGraph.removeUnderlineTriple(Node x, Node y, Node z) voidGraph.removeUnderlineTriple(Node x, Node y, Node z) voidLagGraph.removeUnderlineTriple(Node x, Node y, Node z) voidSemGraph.removeUnderlineTriple(Node x, Node y, Node z) voidTimeLagGraph.removeUnderlineTriple(Node x, Node y, Node z) voidUnderlines.removeUnderlineTriple(Node x, Node y, Node z) Paths.semidirectedPathsFromTo(Node node1, Node node2, int maxLength) booleanDag.setEndpoint(Node from, Node to, Endpoint endPoint) booleanEdgeListGraph.setEndpoint(Node from, Node to, Endpoint endPoint) If there is currently an edge from node1 to node2, sets the endpoint at node2 to the given endpoint; if there is no such edge, adds an edge --# where # is the given endpoint.booleanGraph.setEndpoint(Node from, Node to, Endpoint endPoint) Sets the endpoint type at the 'to' end of the edge from 'from' to 'to' to the given endpoint.booleanLagGraph.setEndpoint(Node from, Node to, Endpoint endPoint) booleanSemGraph.setEndpoint(Node node1, Node node2, Endpoint endpoint) booleanTimeLagGraph.setEndpoint(Node from, Node to, Endpoint endPoint) static Nodestatic NodeEdges.traverseDirected(Node node, Edge edge) For A -> B, given A, returns B; otherwise returns null.static NodeEdges.traverseReverseDirected(Node node, Edge edge) For A -> B, given B, returns A; otherwise returns null.static NodeEdges.traverseSemiDirected(Node node, Edge edge) For A --* B or A o-* B, given A, returns B.static NodeGraphUtils.traverseSemiDirected(Node node, Edge edge) Paths.treksIncludingBidirected(Node node1, Node node2) static EdgeEdges.undirectedEdge(Node nodeA, Node nodeB) Constructs a new undirected edge from nodeA to nodeB (--).Method parameters in edu.cmu.tetrad.graph with type arguments of type NodeModifier and TypeMethodDescriptionConstructs a list of nodes from the givennodeslist at the given indices in that list.MisclassificationUtils.convertNodes(Set<Edge> edges, List<Node> newVariables) booleanPaths.existsInducingPathVisit(Node a, Node b, Node x, Node y, LinkedList<Node> path) booleanPaths.existsSemiDirectedPath(Node node1, Set<Node> nodes) static voidGraphUtils.fciOrientbk(Knowledge knowledge, Graph graph, List<Node> variables) Orients according to background knowledgePaths.getAncestors(List<Node> nodes) Paths.getDescendants(List<Node> nodes) Paths.getMConnectedVars(Node y, Set<Node> z) Paths.getValidOrder(List<Node> initialOrder, boolean forward) Returns a valid causal order for either a DAG or a CPDAG.static voidGraphUtils.gfciExtraEdgeRemovalStep(Graph graph, Graph referenceCpdag, List<Node> nodes, SepsetProducer sepsets) The extra edge removal step for GFCI.GraphSaveLoadUtils.grabLayout(List<Node> nodes) static booleanGraphUtils.isClique(Collection<Node> set, Graph graph) booleanPaths.isMConnectedTo(Node x, Node y, Set<Node> z) Detemrmines whether x and y are d-connected given z.booleanDetemrmines whether x and y are d-connected given z.booleanDetemrmines whether x and y are d-connected given z.booleanDetemrmines whether x and y are d-connected given z.booleanbooleanChecks to see if x and y are d-connected given z.booleanChecks to see if x and y are d-connected given z.booleanChecks to see if x and y are d-connected given z.booleanEdgeListGraph.isMSeparatedFrom(Node x, Node y, Set<Node> z) Determines whether x and y are d-separated given z.booleanDetermines whether two nodes are d-separated given z.booleanEdgeListGraph.isMSeparatedFrom(Set<Node> x, Set<Node> y, Set<Node> z, Map<Node, Set<Node>> ancestors) Determines whether two nodes are d-separated given z.booleanEdgeListGraph.isMSeparatedFrom(Set<Node> x, Set<Node> y, Set<Node> z, Map<Node, Set<Node>> ancestors) Determines whether two nodes are d-separated given z.booleanEdgeListGraph.isMSeparatedFrom(Set<Node> x, Set<Node> y, Set<Node> z, Map<Node, Set<Node>> ancestors) Determines whether two nodes are d-separated given z.booleanPaths.isMSeparatedFrom(Node node1, Node node2, Set<Node> z) Determines whether one n ode is d-separated from another.booleanCheck to see if a set of variables Z satisfies the back-door criterion relative to node x and node y.static GraphGraphSaveLoadUtils.loadGraphBNTPcMatrix(List<Node> vars, DataSet dataSet) voidPaths.makeValidOrder(List<Node> order) GraphUtils.maximalCliques(Graph graph, List<Node> nodes) static GraphGraphSaveLoadUtils.parseGraphXml(nu.xom.Element graphElement, Map<String, Node> nodes) static StringGraphUtils.pathString(Graph graph, List<Node> path) static DagRandomGraph.randomDag(List<Node> nodes, int numLatentConfounders, int maxNumEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected) static GraphRandomGraph.randomGraph(List<Node> nodes, int numLatentConfounders, int maxNumEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected) Defaults to random forward graphs.static GraphRandomGraph.randomGraphRandomForwardEdges(List<Node> nodes, int numLatentConfounders, int numEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected) static GraphRandomGraph.randomGraphRandomForwardEdges(List<Node> nodes, int numLatentConfounders, int numEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected, boolean layoutAsCircle) static GraphRandomGraph.randomGraphUniform(List<Node> nodes, int numLatentConfounders, int maxNumEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected, int numIterations) booleanDag.removeNodes(List<Node> nodes) booleanEdgeListGraph.removeNodes(List<Node> newNodes) Removes any relevant node objects found in this collection.booleanGraph.removeNodes(List<Node> nodes) Iterates through the list and removes any permissible nodes found.booleanLagGraph.removeNodes(List<Node> nodes) booleanSemGraph.removeNodes(List<Node> nodes) booleanTimeLagGraph.removeNodes(List<Node> nodes) static GraphGraphUtils.replaceNodes(Graph originalGraph, List<Node> newVariables) Converts the given graph,originalGraph, to use the new variables (with the same names as the old).GraphUtils.replaceNodes(List<Node> originalNodes, Graph graph) Converts the given list of nodes,originalNodes, to use the replacement nodes for them by the same name in the givengraph.GraphUtils.replaceNodes(List<Node> originalNodes, List<Node> newNodes) Converts the given list of nodes,originalNodes, to use the new variables (with the same names as the old).voidvoidvoidvoidvoidvoidConstructs and returns a subgraph consisting of a given subset of the nodes of this graph together with the edges between them.static GraphConstructors in edu.cmu.tetrad.graph with parameters of type NodeModifierConstructorDescriptionConstructs a new edge by specifying the nodes it connects and the endpoint types.IndependenceFact(Node x, Node y, Node... z) IndependenceFact(Node x, Node y, Set<Node> z) Constructs a triple of nodes.Constructor parameters in edu.cmu.tetrad.graph with type arguments of type Node -
Uses of Node in edu.cmu.tetrad.regression
Methods in edu.cmu.tetrad.regression with parameters of type NodeModifier and TypeMethodDescriptionRegressestargeton theregressors, yielding a regression plane.Regressestargeton theregressors, yielding a regression plane.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.Regresses the target on the given regressors.Method parameters in edu.cmu.tetrad.regression with type arguments of type NodeModifier and TypeMethodDescriptionLogisticRegression.regress(DiscreteVariable x, List<Node> regressors) x must be binary; regressors must be continuous or binary.Regressestargeton theregressors, yielding a regression plane.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.Regresses the target on the given regressors.Constructor parameters in edu.cmu.tetrad.regression with type arguments of type Node -
Uses of Node in edu.cmu.tetrad.search
Methods in edu.cmu.tetrad.search that return NodeModifier and TypeMethodDescriptionCstar.Record.getCauseNode()Cstar.Record.getEffectNode()Return the node associated with the given variable in the graph.default NodeIndependenceTest.getVariable(String name) Returns The variable by the given name.IndTestIod.getVariable(Node node) Returns the variable associated with the given node in the graph.IndTestIod.getVariable(String name) Returns the variable associated with the given name in the graph.MarkovCheck.getVariable(String name) Returns the variable with the given name.Methods in edu.cmu.tetrad.search that return types with arguments of type NodeModifier and TypeMethodDescriptionGiven an initial permutation, 'order,' of the variables, searches for a best permutation of the variables by rearranging the variables in 'order.'Ida.calculateMinimumEffectsOnY(Node y) Returns a map from nodes in V \ {Y} to their minimum effects.Finds the Markov blanket of the given target.Given the target, this returns all the nodes in the Markov Blanket.Returns the Markov blanket variables (not the Markov blanket DAG).Mimbuild.getClustering()Returns the clustering of measured variables, each of which is explained by a single latent.MimbuildTrek.getClustering()The clustering used.Fofc.getClusters()The clusters that are output by the algorithm from the last call to search().Ftfc.getClusters()Returns clusters output by the algorithm from the last call to search().Fas.getNodes()Returns the nodes from the test.Fasd.getNodes()Returns the nodes being searched over.Ida.NodeEffects.getNodes()IFas.getNodes()Returns the nodes searched over.Pcd.getNodes()SvarFas.getNodes()Returns the nodes of the test.PermutationSearch.getOrder()Boss.getParents()Boss.getParents()Sp.getParents()Sp.getParents()SuborderSearch.getParents()The map from nodes to parents resulting from the search.SuborderSearch.getParents()The map from nodes to parents resulting from the search.PcMb.getTargets()Return the targets of the most recent search.Boss.getVariables()Grasp.getVariables()Returns the variables.IndependenceTest.getVariables()IndTestIod.getVariables()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.MarkovCheck.getVariables()Returns the variables of the independence test.PermutationSearch.getVariables()Returns the variables.Sp.getVariables()SuborderSearch.getVariables()The list of all variables, in order.Methods in edu.cmu.tetrad.search with parameters of type NodeModifier and TypeMethodDescriptionvoidSvarFges.addSimilarEdges(Node x, Node y) Ida.calculateMinimumEffectsOnY(Node y) Returns a map from nodes in V \ {Y} to their minimum effects.default IndependenceResultIndependenceTest.checkIndependence(Node x, Node y, Node... z) Checks the independence fact in question and returns and independence result.IndependenceTest.checkIndependence(Node x, Node y, Set<Node> z) IndTestIod.checkIndependence(Node x, Node y, Set<Node> z) Checks the indicated independence fact by pooling available tests for the given variables.default booleanIndependenceTest.determines(Set<Node> z, Node y) Returns true if y is determined the variable in z.booleanIndTestIod.determines(List<Node> z, Node x) Returns true if z contains x.Finds the Markov blanket of the given target.Given the target, this returns all the nodes in the Markov Blanket.Returns the Markov blanket variables (not the Markov blanket DAG).Fas.getAmbiguousTriples(Node node) There are no ambiguous triples for this search, for any nodes.Fasd.getAmbiguousTriples(Node node) Returns an empty list.IFas.getAmbiguousTriples(Node node) Returns the list of ambiguous triples found for a given node.SvarFas.getAmbiguousTriples(Node node) Return the node associated with the given variable in the graph.Ida.getSortedMinEffects(Node y) Returns the minimum effects of X on Y for X in V \ {Y}, sorted downward by minimum effectIndTestIod.getVariable(Node node) Returns the variable associated with the given node in the graph.voidSvarFges.removeSimilarEdges(Node x, Node y) doubleIda.trueEffect(Node x, Node y, Graph trueDag) Calculates the true effect of (x, y) given the true DAG (which must be provided).Method parameters in edu.cmu.tetrad.search with type arguments of type NodeModifier and TypeMethodDescriptionGiven an initial permutation, 'order,' of the variables, searches for a best permutation of the variables by rearranging the variables in 'order.'IndependenceTest.checkIndependence(Node x, Node y, Set<Node> z) IndTestIod.checkIndependence(Node x, Node y, Set<Node> z) Checks the indicated independence fact by pooling available tests for the given variables.default booleanIndependenceTest.determines(Set<Node> z, Node y) Returns true if y is determined the variable in z.booleanIndTestIod.determines(List<Node> z, Node x) Returns true if z contains x.static GraphConstruct a graph given a specification of the parents for each node.static GraphConstruct a graph given a specification of the parents for each node.static GraphConstruct a graph given a specification of the parents for each node.static GraphPermutationSearch.getGraph(List<Node> nodes, Map<Node, Set<Node>> parents, Knowledge knowledge, boolean cpDag) Construct a graph given a specification of the parents for each node.static GraphPermutationSearch.getGraph(List<Node> nodes, Map<Node, Set<Node>> parents, Knowledge knowledge, boolean cpDag) Construct a graph given a specification of the parents for each node.static GraphPermutationSearch.getGraph(List<Node> nodes, Map<Node, Set<Node>> parents, Knowledge knowledge, boolean cpDag) Construct a graph given a specification of the parents for each node.Cstar.getRecords(DataSet dataSet, List<Node> possibleCauses, List<Node> possibleEffects, int topBracket, String path) Returns records for a set of variables with expected number of false positives bounded by q.default IndependenceTestIndependenceTest.indTestSubset(List<Node> vars) Returns an Independence test for a sublist of the variables.IndTestIod.indTestSubset(List<Node> vars) static @NotNull GraphReturns a graph given a coefficient matrix and a list of variables.Discovers all adjacencies in data.Greedy equivalence search: Start from the empty graph, add edges till the model is significant.Mimbuild.search(List<List<Node>> clustering, List<String> latentNames, ICovarianceMatrix measuresCov) Does a Mimbuild search.MimbuildTrek.search(List<List<Node>> clustering, List<String> latentNames, ICovarianceMatrix measuresCov) Does the search and returns the graph.Runs the search using a particular implementation of the fast adjacency search (FAS), over the given sublist of nodes.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.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.Searches for the MB CPDAG for the given targets.Runs the search and returns the RFCI PAG.Searches of a specific sublist of nodes.voidBoss.searchSuborder(List<Node> prefix, List<Node> suborder, Map<Node, GrowShrinkTree> gsts) voidBoss.searchSuborder(List<Node> prefix, List<Node> suborder, Map<Node, GrowShrinkTree> gsts) voidSp.searchSuborder(List<Node> prefix, List<Node> suborder, Map<Node, GrowShrinkTree> gsts) This is the method called by PermutationSearch per tier.voidSp.searchSuborder(List<Node> prefix, List<Node> suborder, Map<Node, GrowShrinkTree> gsts) This is the method called by PermutationSearch per tier.voidSuborderSearch.searchSuborder(List<Node> prefix, List<Node> suborder, Map<Node, GrowShrinkTree> gsts) Searches the suborder.voidSuborderSearch.searchSuborder(List<Node> prefix, List<Node> suborder, Map<Node, GrowShrinkTree> gsts) Searches the suborder.voidvoidvoidPcMb.setVariables(List<Node> variables) Constructor parameters in edu.cmu.tetrad.search with type arguments of type NodeModifierConstructorDescriptionFci(IndependenceTest independenceTest, List<Node> searchVars) Constructor.Constructor.Rfci(IndependenceTest independenceTest, List<Node> searchVars) Constructs a new RFCI search for the given independence test and background knowledge and a list of variables to search over. -
Uses of Node in edu.cmu.tetrad.search.score
Methods in edu.cmu.tetrad.search.score that return NodeModifier and TypeMethodDescriptiondefault NodeScore.getVariable(String targetName) Returns the variable with the given name.Methods in edu.cmu.tetrad.search.score that return types with arguments of type NodeModifier and TypeMethodDescriptionBdeScore.getVariables()Returns the variables of the dataset.BdeuScore.getVariables()Returns the variables of the data.ConditionalGaussianScore.getVariables()Returns the variables of the data.DegenerateGaussianScore.getVariables()DiscreteBicScore.getVariables()Returns the variables.EbicScore.getVariables()Returns the variables for this score.GicScores.getVariables()GraphScore.getVariables()Returns the list of variables.ImagesScore.getVariables()Returns the variables.IndTestScore.getVariables()MvpScore.getVariables()PoissonPriorScore.getVariables()Score.getVariables()The variables of the score.SemBicScore.getVariables()ZsbScore.getVariables()Returns the variables.Methods in edu.cmu.tetrad.search.score with parameters of type NodeModifier and TypeMethodDescriptionbooleanBdeuScore.determines(List<Node> z, Node y) This score does not implement a method to decide whehter a node is determined by its parents.booleanEbicScore.determines(List<Node> z, Node y) Return a judgment of whether the variable in z determine y exactly.booleanGicScores.determines(List<Node> z, Node y) booleanImagesScore.determines(List<Node> z, Node y) Returns the 'determines' judgment from the first score.booleanIndTestScore.determines(List<Node> z, Node y) booleanMvpScore.determines(List<Node> z, Node y) booleanPoissonPriorScore.determines(List<Node> z, Node y) default booleanScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanSemBicScore.determines(List<Node> z, Node y) booleanZsbScore.determines(List<Node> z, Node y) Returns true if the variable in Z determine y.Method parameters in edu.cmu.tetrad.search.score with type arguments of type NodeModifier and TypeMethodDescriptionbooleanBdeuScore.determines(List<Node> z, Node y) This score does not implement a method to decide whehter a node is determined by its parents.booleanEbicScore.determines(List<Node> z, Node y) Return a judgment of whether the variable in z determine y exactly.booleanGicScores.determines(List<Node> z, Node y) booleanImagesScore.determines(List<Node> z, Node y) Returns the 'determines' judgment from the first score.booleanIndTestScore.determines(List<Node> z, Node y) booleanMvpScore.determines(List<Node> z, Node y) booleanPoissonPriorScore.determines(List<Node> z, Node y) default booleanScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanSemBicScore.determines(List<Node> z, Node y) booleanZsbScore.determines(List<Node> z, Node y) Returns true if the variable in Z determine y.voidDiscreteBicScore.setVariables(List<Node> variables) Sets the variables to a new list of the same size.voidGicScores.setVariables(List<Node> variables) voidSemBicScore.setVariables(List<Node> variables) -
Uses of Node in edu.cmu.tetrad.search.test
Methods in edu.cmu.tetrad.search.test that return NodeModifier and TypeMethodDescriptionIndTestFisherZ.getVariable(String name) Returns the variable with the given name.IndTestHsic.getVariable(String name) Returns the variable with the given name.IndTestIndependenceFacts.getVariable(String name) Returns the node with the given name.IndTestProbabilistic.getVariable(String name) IndTestTrekSep.getVariable(String name) Returns the variable with the given name.Kci.getVariable(String name) Returns the variable by the given name.MsepTest.getVariable(String name) Returns the variable with the given name.ScoreIndTest.getVariable(String name) Returns the variable by the given name.Methods in edu.cmu.tetrad.search.test that return types with arguments of type NodeModifier and TypeMethodDescriptionIndTestChiSquare.getVariables()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.IndTestConditionalCorrelation.getVariables()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.IndTestConditionalGaussianLrt.getVariables()Returns the list of variables over which this independence checker is capable of determining independence relations.IndTestDegenerateGaussianLrt.getVariables()Returns the list of searchVariables over which this independence checker is capable of determinining independence relations.IndTestFisherZ.getVariables()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.IndTestFisherZConcatenateResiduals.getVariables()IndTestFisherZFisherPValue.getVariables()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.IndTestGSquare.getVariables()Return 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.IndTestHsic.getVariables()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.IndTestIndependenceFacts.getVariables()Returns the list of variables for the facts.IndTestMulti.getVariables()IndTestMvpLrt.getVariables()Returns the list of searchVariables over which this independence checker is capable of determinining independence relations.IndTestProbabilistic.getVariables()IndTestRegression.getVariables()IndTestTrekSep.getVariables()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.Kci.getVariables()Returns the list of variables over which this independence checker is capable of determinining independence relations.MsepTest.getVariables()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.ScoreIndTest.getVariables()Returns the list of variables over which this independence checker is capable of determinining independence relations.Methods in edu.cmu.tetrad.search.test with parameters of type NodeModifier and TypeMethodDescriptionIndTestChiSquare.checkIndependence(Node x, Node y, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning varNames z.IndTestConditionalCorrelation.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence of x _||_ y | zIndTestConditionalGaussianLrt.checkIndependence(Node x, Node y, Set<Node> _z) Returns and independence result that states whether x _||_y | z and what the p-value of the test is.IndTestDegenerateGaussianLrt.checkIndependence(Node x, Node y, Set<Node> _z) Returns an independence result specifying whether x _||_ y | Z and what its p-values are.IndTestFisherZ.checkIndependence(Node x, Node y, Set<Node> z) Determines whether variable x _||_ y | z given a list of conditioning variables z.IndTestFisherZConcatenateResiduals.checkIndependence(Node x, Node y, Set<Node> _z) Determines whether x _||_ y | z.IndTestFisherZFisherPValue.checkIndependence(Node x, Node y, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestGSquare.checkIndependence(Node x, Node y, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning varNames z.IndTestHsic.checkIndependence(Node y, Node x, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestIndependenceFacts.checkIndependence(Node x, Node y, Set<Node> __z) Checks independence by looking up facts in the list of facts supplied in the constructor.IndTestMulti.checkIndependence(Node x, Node y, Set<Node> z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestMvpLrt.checkIndependence(Node x, Node y, Set<Node> _z) Returns an independence result for x _||_ y | z.IndTestProbabilistic.checkIndependence(Node x, Node y, Node... z) IndTestProbabilistic.checkIndependence(Node x, Node y, Set<Node> _z) IndTestRegression.checkIndependence(Node xVar, Node yVar, Set<Node> zList) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestTrekSep.checkIndependence(Node x, Node y, Set<Node> z) Determines whether variable x is independent of variable y given a list of conditioning variables z.Kci.checkIndependence(Node x, Node y, Set<Node> z) Returns True if the given independence question is judged true, false if not.MsepTest.checkIndependence(Node x, Node y, Set<Node> z) Checks the indicated m-separation fact, msep(x , y | z).ScoreIndTest.checkIndependence(Node x, Node y, Set<Node> z) Determines whether x _||_ y | zbooleanIndTestChiSquare.determines(List<Node> z, Node x) Returns True if the variables z determining the variable z.booleanIndTestConditionalCorrelation.determines(List<Node> z, Node x) booleanIndTestConditionalGaussianLrt.determines(List<Node> z, Node y) Returns true if y is determined the variable in z.booleanIndTestDegenerateGaussianLrt.determines(List<Node> z, Node y) Returns true if y is determined the variable in z.booleanIndTestFisherZ.determines(List<Node> z, Node x) Returns true in case the variable in Z jointly determine x.booleanIndTestFisherZConcatenateResiduals.determines(List<Node> z, Node x) booleanIndTestFisherZFisherPValue.determines(List<Node> z, Node x) booleanIndTestGSquare.determines(Set<Node> _z, Node x) Returns a judgment whether the variables in z determine x.booleanIndTestHsic.determines(List<Node> z, Node x) booleanIndTestIndependenceFacts.determines(List<Node> z, Node y) booleanIndTestMulti.determines(List<Node> z, Node x) booleanIndTestMvpLrt.determines(List<Node> z, Node y) booleanIndTestProbabilistic.determines(Set<Node> z, Node y) booleanIndTestRegression.determines(List<Node> zList, Node xVar) booleanIndTestTrekSep.determines(List<Node> z, Node x) IfisDeterminismAllowed(), defers to IndTestFisherZD; otherwise throws UnsupportedOperationException.booleanKci.determines(List<Node> z, Node y) Returns true if y is determined the variable in z.booleanMsepTest.determines(List<Node> z, Node x1) booleanScoreIndTest.determines(List<Node> z, Node y) Returns true if y is determined the variable in z.doubleConditionalCorrelationIndependence.isIndependent(Node x, Node y, Set<Node> _z) Returns the p-value of the test, x _||_ y | z.booleanMsepTest.isMSeparated(Node x, Node y, Set<Node> z) Auxiliary method to calculate msep(x, y | z) directly from nodes instead of from variables.doubleIndTestProbabilistic.probConstraint(BCInference bci, BCInference.OP op, Node x, Node y, Node[] z, Map<Node, Integer> indices) double[]Calculates the residuals of x regressed nonparametrically onto z.Method parameters in edu.cmu.tetrad.search.test with type arguments of type NodeModifier and TypeMethodDescriptionIndTestChiSquare.checkIndependence(Node x, Node y, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning varNames z.IndTestConditionalCorrelation.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence of x _||_ y | zIndTestConditionalGaussianLrt.checkIndependence(Node x, Node y, Set<Node> _z) Returns and independence result that states whether x _||_y | z and what the p-value of the test is.IndTestDegenerateGaussianLrt.checkIndependence(Node x, Node y, Set<Node> _z) Returns an independence result specifying whether x _||_ y | Z and what its p-values are.IndTestFisherZ.checkIndependence(Node x, Node y, Set<Node> z) Determines whether variable x _||_ y | z given a list of conditioning variables z.IndTestFisherZConcatenateResiduals.checkIndependence(Node x, Node y, Set<Node> _z) Determines whether x _||_ y | z.IndTestFisherZFisherPValue.checkIndependence(Node x, Node y, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestGSquare.checkIndependence(Node x, Node y, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning varNames z.IndTestHsic.checkIndependence(Node y, Node x, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestIndependenceFacts.checkIndependence(Node x, Node y, Set<Node> __z) Checks independence by looking up facts in the list of facts supplied in the constructor.IndTestMulti.checkIndependence(Node x, Node y, Set<Node> z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestMvpLrt.checkIndependence(Node x, Node y, Set<Node> _z) Returns an independence result for x _||_ y | z.IndTestProbabilistic.checkIndependence(Node x, Node y, Set<Node> _z) IndTestRegression.checkIndependence(Node xVar, Node yVar, Set<Node> zList) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestTrekSep.checkIndependence(Node x, Node y, Set<Node> z) Determines whether variable x is independent of variable y given a list of conditioning variables z.Kci.checkIndependence(Node x, Node y, Set<Node> z) Returns True if the given independence question is judged true, false if not.MsepTest.checkIndependence(Node x, Node y, Set<Node> z) Checks the indicated m-separation fact, msep(x , y | z).ScoreIndTest.checkIndependence(Node x, Node y, Set<Node> z) Determines whether x _||_ y | zbooleanIndTestChiSquare.determines(List<Node> z, Node x) Returns True if the variables z determining the variable z.booleanIndTestConditionalCorrelation.determines(List<Node> z, Node x) booleanIndTestConditionalGaussianLrt.determines(List<Node> z, Node y) Returns true if y is determined the variable in z.booleanIndTestDegenerateGaussianLrt.determines(List<Node> z, Node y) Returns true if y is determined the variable in z.booleanIndTestFisherZ.determines(List<Node> z, Node x) Returns true in case the variable in Z jointly determine x.booleanIndTestFisherZConcatenateResiduals.determines(List<Node> z, Node x) booleanIndTestFisherZFisherPValue.determines(List<Node> z, Node x) booleanIndTestGSquare.determines(Set<Node> _z, Node x) Returns a judgment whether the variables in z determine x.booleanIndTestHsic.determines(List<Node> z, Node x) booleanIndTestIndependenceFacts.determines(List<Node> z, Node y) booleanIndTestMulti.determines(List<Node> z, Node x) booleanIndTestMvpLrt.determines(List<Node> z, Node y) booleanIndTestProbabilistic.determines(Set<Node> z, Node y) booleanIndTestRegression.determines(List<Node> zList, Node xVar) booleanIndTestTrekSep.determines(List<Node> z, Node x) IfisDeterminismAllowed(), defers to IndTestFisherZD; otherwise throws UnsupportedOperationException.booleanKci.determines(List<Node> z, Node y) Returns true if y is determined the variable in z.booleanMsepTest.determines(List<Node> z, Node x1) booleanScoreIndTest.determines(List<Node> z, Node y) Returns true if y is determined the variable in z.IndTestChiSquare.indTestSubset(List<Node> nodes) Creates a new IndTestChiSquare for a subset of the nodes.IndTestConditionalCorrelation.indTestSubset(List<Node> vars) IndTestConditionalGaussianLrt.indTestSubset(List<Node> vars) IndTestDegenerateGaussianLrt.indTestSubset(List<Node> vars) IndTestFisherZ.indTestSubset(List<Node> vars) Creates a new independence test instance for a subset of the variables.IndTestFisherZConcatenateResiduals.indTestSubset(List<Node> vars) IndTestFisherZFisherPValue.indTestSubset(List<Node> vars) IndTestGSquare.indTestSubset(List<Node> vars) Creates a new IndTestGSquare for a sublist of the variables.IndTestHsic.indTestSubset(List<Node> vars) Creates a new IndTestHsic instance for a subset of the variables.IndTestIndependenceFacts.indTestSubset(List<Node> vars) IndTestMulti.indTestSubset(List<Node> vars) IndTestMvpLrt.indTestSubset(List<Node> vars) Returns an independence test for a sublist of the searchVariables.IndTestProbabilistic.indTestSubset(List<Node> vars) IndTestRegression.indTestSubset(List<Node> vars) Creates a new IndTestCramerT instance for a subset of the variables.IndTestTrekSep.indTestSubset(List<Node> vars) Creates a new independence test instance for a sublist of the variables.Kci.indTestSubset(List<Node> vars) MsepTest.indTestSubset(List<Node> vars) Returns a test over a subset of the variables.ScoreIndTest.indTestSubset(List<Node> vars) doubleConditionalCorrelationIndependence.isIndependent(Node x, Node y, Set<Node> _z) Returns the p-value of the test, x _||_ y | z.booleanMsepTest.isMSeparated(Node x, Node y, Set<Node> z) Auxiliary method to calculate msep(x, y | z) directly from nodes instead of from variables.doubleIndTestProbabilistic.probConstraint(BCInference bci, BCInference.OP op, Node x, Node y, Node[] z, Map<Node, Integer> indices) double[]Calculates the residuals of x regressed nonparametrically onto z.voidIndTestFisherZ.setVariables(List<Node> variables) Sets the variables to a new list of the same size.voidIndTestTrekSep.setVariables(List<Node> variables) Sets the varialbe to this list (of the same length).Constructor parameters in edu.cmu.tetrad.search.test with type arguments of type NodeModifierConstructorDescriptionIndTestFisherZ(Matrix data, List<Node> variables, double alpha) Constructs a new Fisher Z independence test with the listed arguments.IndTestHsic(Matrix data, List<Node> variables, double alpha) Constructs a new HSIC Independence test.IndTestTrekSep(ICovarianceMatrix covMatrix, double alpha, List<List<Node>> clustering, List<Node> latents) Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.MsepTest(IndependenceFacts facts, List<Node> variables) Constructor. -
Uses of Node in edu.cmu.tetrad.search.utils
Methods in edu.cmu.tetrad.search.utils that return NodeModifier and TypeMethodDescriptionTeyssierScorer.get(int j) Returns the node at index j in pi.Tetrad.getI()Tetrad.getJ()Tetrad.getK()Tetrad.getL()GrowShrinkTree.getNode()static NodeMethods in edu.cmu.tetrad.search.utils that return types with arguments of type NodeModifier and TypeMethodDescriptionClusterUtils.clustersToPartition(Clusters clusters, List<Node> variables) MimUtils.convertToClusters2(Graph clusterGraph) Returns the parents of the node x.Retrieves the sepset previously set for {a, b}, or null if no such set was previously set.TeyssierScorer.getAdjacentNodes(Node v) Returns the nodes adjacent to v.TeyssierScorer.getAncestors(Node node) TeyssierScorer.getChildren(int p) Returns the children of a node v.TeyssierScorer.getChildren(Node v) Returns the children of a node v.PossibleMConnectingPath.getConditions()TeyssierScorer.getEdges()Returns a list of edges for the current graph as a list of ordered pairs.GrowShrinkTree.getFirstLayer()GrowShrinkTree.getForbidden()Tetrad.getNodes()TeyssierScorer.getOrderShallow()Returns the current permutation without making a copy.TeyssierScorer.getParents(int p) Returns the parents of the node at index p.TeyssierScorer.getParents(Node v) Returns the parents of a node v.PossibleMConnectingPath.getPath()TeyssierScorer.getPi()TeyssierScorer.getPrefix(int i) GraphSearchUtils.getReachableNodes(List<Node> initialNodes, LegalPairs legalPairs, List<Node> c, List<Node> d, Graph graph, int maxPathLength) GrowShrinkTree.getRequired()Returns the list of sepset for {a, b}.PossibleMsepFci.getSepset(IndependenceTest test, Node node1, Node node2) Pick out the sepset from among adj(i) or adj(k) with the highest p value.Pick out the sepset from among adj(i) or adj(k) with the highest score value.Pick out the sepset from among adj(i) or adj(k) with the highest p value.SepsetsConservative.getSepsetsLists(Node x, Node y, Node z, IndependenceTest test, int depth, boolean verbose) TeyssierScorer.getShuffledVariables()TeyssierScorer.getSkeleton()FciOrient.getUcCirclePaths(Node n1, Node n2, Graph graph) Gets a list of every uncovered circle path between two nodes in the graph by iterating through the uncovered partially directed undirectedPaths and only keeping the circle undirectedPaths.FciOrient.getUcPdPaths(Node n1, Node n2, Graph graph) Gets a list of every uncovered partially directed path between two nodes in the graph.Bes.getVariables()Returns the variables being searched over.BesPermutation.getVariables()Returns the variables.DagSepsets.getVariables()Returns the nodes in the DAG.DeltaSextadTest.getVariables()Returns the variables of the data being used.GrowShrinkTree.getVariables()SepsetProducer.getVariables()SepsetsConservative.getVariables()SepsetsGreedy.getVariables()SepsetsPossibleMsep.getVariables()SepsetsSet.getVariables()TetradTest.getVariables()TetradTestContinuous.getVariables()TetradTestDiscrete.getVariables()TetradTestPopulation.getVariables()GraphoidAxioms.GraphoidIndFact.getX()GraphoidAxioms.GraphoidIndFact.getY()GraphoidAxioms.GraphoidIndFact.getZ()MeekRules.orientImplied(Graph graph) Uses the Meek rules to do as many orientations in the given graph as possible.ClusterSignificance.variablesForIndices(List<Integer> cluster, List<Node> variables) Methods in edu.cmu.tetrad.search.utils with parameters of type NodeModifier and TypeMethodDescriptionbooleanReturns True iff a is adjacent to b in the current graph.static voidGraphSearchUtils.basicCpdagRestricted2(Graph graph, Node node) booleanReturns true iff [a, b, c] is a collider.static StringLogUtilsSearch.colliderOrientedMsg(Node x, Node y, Node z) static Stringstatic StringLogUtilsSearch.colliderOrientedMsg(String note, Node x, Node y, Node z) doubleCalculates the partial correlation of x and y conditional on the nodes in z recursively.booleanTeyssierScorer.coveredEdge(Node x, Node y) Returns true iff x->y or y->x is a covered edge.voida method to search "back from a" to find a DDP.voida method to search "back from a" to find a DDP.static StringLogUtilsSearch.dependenceFactMsg(Node x, Node y, Set<Node> condSet, double pValue) static StringLogUtilsSearch.determinismDetected(Set<Node> sepset, Node x) booleanOrients the edges inside the definte discriminating path triangle.static booleanDagToPag.existsInducingPathInto(Node x, Node y, Graph graph) static booleanTsDagToPag.existsInducingPathInto(Node x, Node y, Graph graph, Knowledge knowledge) static booleanTsDagToPag.existsInducingPathVisitts(Graph graph, Node a, Node b, Node x, Node y, LinkedList<Node> path, Knowledge knowledge) static List<PossibleMConnectingPath>PossibleMConnectingPath.findMConnectingPaths(Graph pag, Node x, Node y, Collection<Node> z) Finds all possible D-connection undirectedPaths as sub-graphs of the pag given at construction time from x to y given z.static List<PossibleMConnectingPath>PossibleMConnectingPath.findMConnectingPathsOfLength(Graph pag, Node x, Node y, Collection<Node> z, Integer length) 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.MbUtils.generateMbDags(Graph mbCPDAG, boolean orientBidirectedEdges, IndependenceTest test, int depth, Node target) Generates the list of MB DAGs consistent with the MB CPDAG returned by the previous search.Returns the parents of the node x.Retrieves the sepset previously set for {a, b}, or null if no such set was previously set.TeyssierScorer.getAdjacentNodes(Node v) Returns the nodes adjacent to v.TeyssierScorer.getAncestors(Node node) TeyssierScorer.getChildren(Node v) Returns the children of a node v.GraphSearchUtils.getCpcTripleType(Node x, Node y, Node z, IndependenceTest test, int depth, Graph graph) TeyssierScorer.getParents(Node v) Returns the parents of a node v.doubleLooks up the p-value for {x, y}static StringLogUtilsSearch.getScoreFact(Node i, List<Node> parents) Returns the list of sepset for {a, b}.PossibleMsepFci.getSepset(IndependenceTest test, Node node1, Node node2) Pick out the sepset from among adj(i) or adj(k) with the highest p value.Pick out the sepset from among adj(i) or adj(k) with the highest score value.Pick out the sepset from among adj(i) or adj(k) with the highest p value.SepsetsConservative.getSepsetsLists(Node x, Node y, Node z, IndependenceTest test, int depth, boolean verbose) FciOrient.getUcCirclePaths(Node n1, Node n2, Graph graph) Gets a list of every uncovered circle path between two nodes in the graph by iterating through the uncovered partially directed undirectedPaths and only keeping the circle undirectedPaths.FciOrient.getUcPdPaths(Node n1, Node n2, Graph graph) Gets a list of every uncovered partially directed path between two nodes in the graph.static StringLogUtilsSearch.independenceFact(Node x, Node y, Set<Node> condSet) static StringLogUtilsSearch.independenceFactMsg(Node x, Node y, Set<Node> condSet, double pValue) intReturn the index of v in the current permutation.static booleanFciOrient.isArrowheadAllowed(Node x, Node y, Graph graph, Knowledge knowledge) booleanGrowShrinkTree.isForbidden(Node node) booleanDagSepsets.isIndependent(Node a, Node b, Set<Node> c) Returns true just in case msep(a, b | c) in the DAG.booleanSepsetProducer.isIndependent(Node d, Node c, Set<Node> path) booleanSepsetsConservative.isIndependent(Node a, Node b, Set<Node> c) booleanSepsetsGreedy.isIndependent(Node a, Node b, Set<Node> c) booleanSepsetsPossibleMsep.isIndependent(Node d, Node c, Set<Node> path) booleanSepsetsSet.isIndependent(Node a, Node b, Set<Node> c) static booleanResolveSepsets.isIndependentPooled(ResolveSepsets.Method method, List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Tests for independence using one of the pooled methodsstatic booleanResolveSepsets.isIndependentPooledAverage(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by taking the average p valuestatic booleanResolveSepsets.isIndependentPooledAverageTest(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by taking the average test statistic CURRENTLY ONLY WORKS FOR CHISQUARE TESTstatic booleanResolveSepsets.isIndependentPooledFisher(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Fisher's method.static booleanResolveSepsets.isIndependentPooledFisher2(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Eliminates from considerations independence tests that cannot be evaluated (due to missing variables mainly).static booleanResolveSepsets.isIndependentPooledMudholkerGeorge(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Mudholker and George's methodstatic booleanResolveSepsets.isIndependentPooledMudholkerGeorge2(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) The same as isIndepenentPooledMudholkerGeoerge, except that only available independence tests are used.static booleanResolveSepsets.isIndependentPooledRandom(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by randomly selecting a p valuestatic booleanResolveSepsets.isIndependentPooledStouffer(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Stouffer et al.'s methodstatic booleanResolveSepsets.isIndependentPooledTippett(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Tippett's methodstatic booleanResolveSepsets.isIndependentPooledWilkinson(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet, int r) Checks independence from pooled samples using Wilkinson's methodstatic booleanResolveSepsets.isIndependentPooledWorsleyFriston(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Worsley and Friston's methodbooleanLegalPairs.isLegalFirstEdge(Node x, Node y) booleanbooleanGrowShrinkTree.isRequired(Node node) booleanDagSepsets.isUnshieldedCollider(Node i, Node j, Node k) True iff i*-*j*-*k is an unshielded collider.booleanSepsetProducer.isUnshieldedCollider(Node i, Node j, Node k) booleanSepsetsConservative.isUnshieldedCollider(Node i, Node j, Node k) booleanSepsetsGreedy.isUnshieldedCollider(Node i, Node j, Node k) booleanSepsetsPossibleMsep.isUnshieldedCollider(Node i, Node j, Node k) booleanSepsetsSet.isUnshieldedCollider(Node i, Node j, Node k) voidMoves v to a new index.static voidPcCommon.orientCollider(Node x, Node y, Node z, PcCommon.ConflictRule conflictRule, Graph graph) Orient a single unshielded triple, x*-*y*-*z, in a graph.booleanvoidvoidTries to apply Zhang's rule R10 to a pair of nodes A and C which are assumed to be such that Ao->C.voidbooleanTries to apply Zhang's rule R8 to a pair of nodes A and C which are assumed to be such that Ao->C.booleanTries to apply Zhang's rule R9 to a pair of nodes A and C which are assumed to be such that Ao->C.voidSets the sepset for {x, y} to be z.voidSepsetMap.set(Node x, LinkedHashSet<Node> z) Sets the parents of x to the (ordered) set z.voidKernel.setDefaultBw(DataSet dataset, Node node) Sets bandwidth from data using default methodvoidKernelGaussian.setDefaultBw(DataSet dataset, Node node) Default setting of bandwidth based on median distance heuristicvoidKernelGaussian.setMedianBandwidth(DataSet dataset, Node node) Sets the bandwidth of the kernel to median distance between two points in the given vectorbooleanSwaps m and n in the permutation.voidPerforms a tuck operation.booleanReturns true iff [a, b, c] is a triangle.static voidMbUtils.trimEdgesAmongParents(Graph graph, Node target) Removes edges among the parents of the target.static voidMbUtils.trimEdgesAmongParentsOfChildren(Graph graph, Node target) Removes edges among the parents of children of the target.static voidMbUtils.trimToAdjacents(Graph graph, Node target) Trims the graph to just the adjacents of the target.static voidMbUtils.trimToMbNodes(Graph graph, Node target, boolean includeBidirected) Trims the graph to the target, the parents and children of the target, and the parents of the children of the target.booleanMethod parameters in edu.cmu.tetrad.search.utils with type arguments of type NodeModifier and TypeMethodDescriptionvoidRuns BES for a graph over the given list of variablesvoidRuns BES.booleanTrue iff the nodes in W form a clique in the current DAG.ClusterUtils.clustersToPartition(Clusters clusters, List<Node> variables) static Stringstatic List<int[]>static ClustersMimUtils.convertToClusters(Graph clusterGraph, List<Node> measuredVariables) Converts a disconnected multiple indicator model into a set of clusters.doubleCalculates the partial correlation of x and y conditional on the nodes in z recursively.static StringLogUtilsSearch.dependenceFactMsg(Node x, Node y, Set<Node> condSet, double pValue) static StringLogUtilsSearch.determinismDetected(Set<Node> sepset, Node x) static booleanTsDagToPag.existsInducingPathVisitts(Graph graph, Node a, Node b, Node x, Node y, LinkedList<Node> path, Knowledge knowledge) voidFciOrient.fciOrientbk(Knowledge bk, Graph graph, List<Node> variables) Orients according to background knowledgestatic List<PossibleMConnectingPath>PossibleMConnectingPath.findMConnectingPaths(Graph pag, Node x, Node y, Collection<Node> z) Finds all possible D-connection undirectedPaths as sub-graphs of the pag given at construction time from x to y given z.static List<PossibleMConnectingPath>PossibleMConnectingPath.findMConnectingPathsOfLength(Graph pag, Node x, Node y, Collection<Node> z, Integer length) 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.GraphSearchUtils.getReachableNodes(List<Node> initialNodes, LegalPairs legalPairs, List<Node> c, List<Node> d, Graph graph, int maxPathLength) static StringLogUtilsSearch.getScoreFact(int i, int[] parents, List<Node> variables) static StringLogUtilsSearch.getScoreFact(Node i, List<Node> parents) static StringLogUtilsSearch.independenceFact(Node x, Node y, Set<Node> condSet) static StringLogUtilsSearch.independenceFactMsg(Node x, Node y, Set<Node> condSet, double pValue) booleanDagSepsets.isIndependent(Node a, Node b, Set<Node> c) Returns true just in case msep(a, b | c) in the DAG.booleanSepsetProducer.isIndependent(Node d, Node c, Set<Node> path) booleanSepsetsConservative.isIndependent(Node a, Node b, Set<Node> c) booleanSepsetsGreedy.isIndependent(Node a, Node b, Set<Node> c) booleanSepsetsPossibleMsep.isIndependent(Node d, Node c, Set<Node> path) booleanSepsetsSet.isIndependent(Node a, Node b, Set<Node> c) static booleanResolveSepsets.isIndependentPooled(ResolveSepsets.Method method, List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Tests for independence using one of the pooled methodsstatic booleanResolveSepsets.isIndependentPooledAverage(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by taking the average p valuestatic booleanResolveSepsets.isIndependentPooledAverageTest(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by taking the average test statistic CURRENTLY ONLY WORKS FOR CHISQUARE TESTstatic booleanResolveSepsets.isIndependentPooledFisher(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Fisher's method.static booleanResolveSepsets.isIndependentPooledFisher2(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Eliminates from considerations independence tests that cannot be evaluated (due to missing variables mainly).static booleanResolveSepsets.isIndependentPooledMudholkerGeorge(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Mudholker and George's methodstatic booleanResolveSepsets.isIndependentPooledMudholkerGeorge2(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) The same as isIndepenentPooledMudholkerGeoerge, except that only available independence tests are used.static booleanResolveSepsets.isIndependentPooledRandom(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by randomly selecting a p valuestatic booleanResolveSepsets.isIndependentPooledStouffer(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Stouffer et al.'s methodstatic booleanResolveSepsets.isIndependentPooledTippett(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Tippett's methodstatic booleanResolveSepsets.isIndependentPooledWilkinson(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet, int r) Checks independence from pooled samples using Wilkinson's methodstatic booleanResolveSepsets.isIndependentPooledWorsleyFriston(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Worsley and Friston's methodbooleanstatic voidvoidFciOrient.orientTailPath(List<Node> path, Graph graph) Orients every edge on a path as undirected (i.e.static ClustersClusterUtils.partitionToClusters(List<List<Node>> partition) static voidGraphSearchUtils.pcOrientbk(Knowledge bk, Graph graph, List<Node> nodes) Orients according to background knowledge.doubleScores the given permutation.Runs the search over the given list of nodes only, returning the serach graph.voidSets the sepset for {x, y} to be z.voidSepsetMap.set(Node x, LinkedHashSet<Node> z) Sets the parents of x to the (ordered) set z.voidGrowShrinkTree.setKnowledge(List<Node> required, List<Node> forbidden) doubledoublestatic NodeConstructors in edu.cmu.tetrad.search.utils with parameters of type NodeModifierConstructorDescriptionKernelGaussian(DataSet dataset, Node node) Creates a new Gaussian kernel using the median distance between points to set the bandwidthConstructor parameters in edu.cmu.tetrad.search.utils with type arguments of type NodeModifierConstructorDescriptionClusterSignificance(List<Node> variables, DataModel dataModel) GraphoidAxioms(Set<GraphoidAxioms.GraphoidIndFact> facts, List<Node> nodes) Constructor.GraphoidAxioms(Set<GraphoidAxioms.GraphoidIndFact> facts, List<Node> nodes, Map<GraphoidAxioms.GraphoidIndFact, String> textSpecs) Constructor.PartialCorrelation(List<Node> nodes, Matrix cov, int sampleSize) Constructor. -
Uses of Node in edu.cmu.tetrad.search.work_in_progress
Methods in edu.cmu.tetrad.search.work_in_progress that return NodeModifier and TypeMethodDescriptionSextad.getI()Sextad.getJ()Sextad.getK()Sextad.getL()Sextad.getM()Sextad.getN()IndTestFisherZRecursive.getVariable(String name) IndTestPositiveCorr.getVariable(String name) IndTestSepsetDci.getVariable(Node node) IndTestSepsetDci.getVariable(String name) ProbabilisticMapIndependence.getVariable(String name) Methods in edu.cmu.tetrad.search.work_in_progress that return types with arguments of type NodeModifier and TypeMethodDescriptionOtherPermAlgs.esp(@NotNull TeyssierScorer scorer) Searches for the Markov blanket of the node by the given name.OtherPermAlgs.gasp(@NotNull TeyssierScorer scorer) Retrieves the sepset previously set for {x, y}, or null if no such set was previously set.VcFas.getApparentlyNonadjacencies()DMSearch.LatentStructure.getLatentEffects(Node latent) DMSearch.LatentStructure.getLatents()Fas2.getNodes()Fas3.getNodes()Returns the nodes from the test.FasFdr.getNodes()Sextad.getNodes()VcFas.getNodes()MagSemBicScore.getOrder()Returns the order.DMSearch.LatentStructure.getOutputs(Node latent) SepsetMapDci.getSeparatedPairs()Retrieves the set of all condioning sets for {x, y} or null if no such set was ever setGraspTol.getVariables()IndTestCramerT.getVariables()IndTestFisherZGeneralizedInverse.getVariables()IndTestFisherZPercentIndependent.getVariables()IndTestFisherZRecursive.getVariables()IndTestMixedMultipleTTest.getVariables()IndTestMnlrLr.getVariables()IndTestMultinomialLogisticRegression.getVariables()IndTestPositiveCorr.getVariables()IndTestSepsetDci.getVariables()IndTestUniformScatter.getVariables()MagSemBicScore.getVariables()Returns the list of variables.MnlrScore.getVariables()Returns the variables.OtherPermAlgs.getVariables()ProbabilisticMapIndependence.getVariables()SemBicScoreDeterministic.getVariables()GraspTol.grasp(@NotNull TeyssierScorer scorer) OtherPermAlgs.rcg(@NotNull TeyssierScorer scorer) OtherPermAlgs.sp(@NotNull TeyssierScorer scorer) Methods in edu.cmu.tetrad.search.work_in_progress with parameters of type NodeModifier and TypeMethodDescriptionvoidAdd another orient operation to the GraphChange.voidDMSearch.LatentStructure.addRecord(Node latent, SortedSet<Node> inputs, SortedSet<Node> outputs, SortedSet<Node> latentEffects) IndTestCramerT.checkIndependence(Node x, Node y, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestFisherZGeneralizedInverse.checkIndependence(Node xVar, Node yVar, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestFisherZPercentIndependent.checkIndependence(Node x, Node y, Set<Node> _z) IndTestFisherZRecursive.checkIndependence(Node x, Node y, Set<Node> z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestMixedMultipleTTest.checkIndependence(Node x, Node y, Set<Node> z) IndTestMnlrLr.checkIndependence(Node x, Node y, Set<Node> _z) IndTestMultinomialLogisticRegression.checkIndependence(Node x, Node y, Set<Node> z) IndTestPositiveCorr.checkIndependence(Node x0, Node y0, Set<Node> _z0) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestSepsetDci.checkIndependence(Node x, Node y, Set<Node> z) Checks the indicated independence fact.IndTestUniformScatter.checkIndependence(Node x, Node y, Set<Node> z) ProbabilisticMapIndependence.checkIndependence(Node x, Node y, Node... z) ProbabilisticMapIndependence.checkIndependence(Node x, Node y, Set<Node> _z) booleanDMSearch.LatentStructure.containsLatent(Node latent) booleanIndTestCramerT.determines(List<Node> z, Node x) booleanIndTestFisherZGeneralizedInverse.determines(List<Node> zList, Node xVar) Returns true just in case the varialbe in zList determine xVar.booleanIndTestFisherZPercentIndependent.determines(List z, Node x) booleanIndTestFisherZRecursive.determines(Set<Node> _z, Node x) IfisDeterminismAllowed(), deters to IndTestFisherZD; otherwise throws UnsupportedOperationException.booleanIndTestMixedMultipleTTest.determines(List<Node> z, Node y) booleanIndTestMnlrLr.determines(List<Node> z, Node y) booleanIndTestMultinomialLogisticRegression.determines(List<Node> z, Node y) booleanIndTestPositiveCorr.determines(List<Node> z, Node x) IfisDeterminismAllowed(), deters to IndTestFisherZD; otherwise throws UnsupportedOperationException.booleanIndTestSepsetDci.determines(List<Node> z, Node x1) booleanProbabilisticMapIndependence.determines(Set<Node> z, Node y) booleanSemBicScoreDeterministic.determines(List<Node> z, Node y) Searches for the Markov blanket of the node by the given name.static voidSampleVcpc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidSampleVcpcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidVcPc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidVcPcAlt.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidVcPcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) Retrieves the sepset previously set for {x, y}, or null if no such set was previously set.Fas2.getAmbiguousTriples(Node node) Fas3.getAmbiguousTriples(Node node) There are no ambiguous triples for this search, for any nodes.FasFdr.getAmbiguousTriples(Node node) DMSearch.LatentStructure.getLatentEffects(Node latent) DMSearch.LatentStructure.getOutputs(Node latent) VcPc.getPopulationTripleType(Node x, Node y, Node z, IndependenceTest test, int depth, Graph graph, boolean verbose) VcPcFast.getPopulationTripleType(Node x, Node y, Node z, IndependenceTest test, int depth, Graph graph, boolean verbose) Retrieves the set of all condioning sets for {x, y} or null if no such set was ever setIndTestSepsetDci.getVariable(Node node) static booleanSampleVcpcFast.isArrowheadAllowed1(Node from, Node to, Knowledge knowledge) static booleanVcPc.isArrowheadAllowed1(Node from, Node to, Knowledge knowledge) static booleanResolveSepsetsDci.isIndependentPooled(ResolveSepsetsDci.Method method, List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Tests for independence using one of the pooled methodsstatic booleanResolveSepsetsDci.isIndependentPooledAverage(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by taking the average p valuestatic booleanResolveSepsetsDci.isIndependentPooledAverageTest(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by taking the average test statistic CURRENTLY ONLY WORKS FOR CHISQUARE TESTstatic booleanResolveSepsetsDci.isIndependentPooledFisher(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Fisher's method.static booleanResolveSepsetsDci.isIndependentPooledFisher2(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Eliminates from considerations independence tests that cannot be evaluated (due to missing variables mainly).static booleanResolveSepsetsDci.isIndependentPooledMudholkerGeorge(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Mudholker and George's methodstatic booleanResolveSepsetsDci.isIndependentPooledMudholkerGeorge2(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) The same as isIndepenentPooledMudholkerGeoerge, except that only available independence tests are used.static booleanResolveSepsetsDci.isIndependentPooledRandom(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by randomly selecting a p valuestatic booleanResolveSepsetsDci.isIndependentPooledStouffer(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Stouffer et al.'s methodstatic booleanResolveSepsetsDci.isIndependentPooledTippett(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Tippett's methodstatic booleanResolveSepsetsDci.isIndependentPooledWilkinson(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet, int r) Checks independence from pooled samples using Wilkinson's methodstatic booleanResolveSepsetsDci.isIndependentPooledWorsleyFriston(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Worsley and Friston's methoddoubleProbabilisticMapIndependence.probConstraint(BCInference.OP op, Node x, Node y, Node[] z) voidDMSearch.LatentStructure.removeLatent(Node latent) voidSets the sepset for {x, y} to be z.voidSepsetMapDci.set(Node x, LinkedHashSet<Node> z) Method parameters in edu.cmu.tetrad.search.work_in_progress with type arguments of type NodeModifier and TypeMethodDescriptionvoidDMSearch.LatentStructure.addRecord(Node latent, SortedSet<Node> inputs, SortedSet<Node> outputs, SortedSet<Node> latentEffects) ResolveSepsetsDci.allNodePairs(List<Node> nodes) Generates NodePairs of all possible pairs of nodes from given list of nodes.IndTestCramerT.checkIndependence(Node x, Node y, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestFisherZGeneralizedInverse.checkIndependence(Node xVar, Node yVar, Set<Node> _z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestFisherZPercentIndependent.checkIndependence(Node x, Node y, Set<Node> _z) IndTestFisherZRecursive.checkIndependence(Node x, Node y, Set<Node> z) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestMixedMultipleTTest.checkIndependence(Node x, Node y, Set<Node> z) IndTestMnlrLr.checkIndependence(Node x, Node y, Set<Node> _z) IndTestMultinomialLogisticRegression.checkIndependence(Node x, Node y, Set<Node> z) IndTestPositiveCorr.checkIndependence(Node x0, Node y0, Set<Node> _z0) Determines whether variable x is independent of variable y given a list of conditioning variables z.IndTestSepsetDci.checkIndependence(Node x, Node y, Set<Node> z) Checks the indicated independence fact.IndTestUniformScatter.checkIndependence(Node x, Node y, Set<Node> z) ProbabilisticMapIndependence.checkIndependence(Node x, Node y, Set<Node> _z) booleanIndTestCramerT.determines(List<Node> z, Node x) booleanIndTestFisherZGeneralizedInverse.determines(List<Node> zList, Node xVar) Returns true just in case the varialbe in zList determine xVar.booleanIndTestFisherZRecursive.determines(Set<Node> _z, Node x) IfisDeterminismAllowed(), deters to IndTestFisherZD; otherwise throws UnsupportedOperationException.booleanIndTestMixedMultipleTTest.determines(List<Node> z, Node y) booleanIndTestMnlrLr.determines(List<Node> z, Node y) booleanIndTestMultinomialLogisticRegression.determines(List<Node> z, Node y) booleanIndTestPositiveCorr.determines(List<Node> z, Node x) IfisDeterminismAllowed(), deters to IndTestFisherZD; otherwise throws UnsupportedOperationException.booleanIndTestSepsetDci.determines(List<Node> z, Node x1) booleanProbabilisticMapIndependence.determines(Set<Node> z, Node y) booleanSemBicScoreDeterministic.determines(List<Node> z, Node y) static voidSampleVcpc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidSampleVcpc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidSampleVcpcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidSampleVcpcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidVcPc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidVcPc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidVcPcAlt.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidVcPcAlt.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidVcPcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) static voidVcPcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) IndTestCramerT.indTestSubset(List<Node> vars) Creates a new IndTestCramerT instance for a subset of the variables.IndTestFisherZGeneralizedInverse.indTestSubset(List<Node> vars) Creates a new IndTestCramerT instance for a subset of the variables.IndTestFisherZPercentIndependent.indTestSubset(List<Node> vars) IndTestFisherZRecursive.indTestSubset(List<Node> vars) Creates a new independence test instance for a subset of the variables.IndTestMixedMultipleTTest.indTestSubset(List<Node> vars) IndTestMnlrLr.indTestSubset(List<Node> vars) IndTestMultinomialLogisticRegression.indTestSubset(List<Node> vars) IndTestPositiveCorr.indTestSubset(List<Node> vars) Creates a new independence test instance for a subset of the variables.IndTestSepsetDci.indTestSubset(List<Node> vars) Required by IndependenceTest.ProbabilisticMapIndependence.indTestSubset(List<Node> vars) static booleanResolveSepsetsDci.isIndependentPooled(ResolveSepsetsDci.Method method, List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Tests for independence using one of the pooled methodsstatic booleanResolveSepsetsDci.isIndependentPooledAverage(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by taking the average p valuestatic booleanResolveSepsetsDci.isIndependentPooledAverageTest(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by taking the average test statistic CURRENTLY ONLY WORKS FOR CHISQUARE TESTstatic booleanResolveSepsetsDci.isIndependentPooledFisher(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Fisher's method.static booleanResolveSepsetsDci.isIndependentPooledFisher2(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Eliminates from considerations independence tests that cannot be evaluated (due to missing variables mainly).static booleanResolveSepsetsDci.isIndependentPooledMudholkerGeorge(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Mudholker and George's methodstatic booleanResolveSepsetsDci.isIndependentPooledMudholkerGeorge2(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) The same as isIndepenentPooledMudholkerGeoerge, except that only available independence tests are used.static booleanResolveSepsetsDci.isIndependentPooledRandom(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples by randomly selecting a p valuestatic booleanResolveSepsetsDci.isIndependentPooledStouffer(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Stouffer et al.'s methodstatic booleanResolveSepsetsDci.isIndependentPooledTippett(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Tippett's methodstatic booleanResolveSepsetsDci.isIndependentPooledWilkinson(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet, int r) Checks independence from pooled samples using Wilkinson's methodstatic booleanResolveSepsetsDci.isIndependentPooledWorsleyFriston(List<IndependenceTest> independenceTests, Node x, Node y, Set<Node> condSet) Checks independence from pooled samples using Worsley and Friston's methodbooleanDetermines whether one trek is a subtrek of another trekDiscovers all adjacencies in data.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.voidSets the sepset for {x, y} to be z.voidSepsetMapDci.set(Node x, LinkedHashSet<Node> z) voidSets the order.voidIndTestFisherZRecursive.setVariables(List<Node> variables) voidIndTestPositiveCorr.setVariables(List<Node> variables) voidSemBicScoreDeterministic.setVariables(List<Node> variables) Constructors in edu.cmu.tetrad.search.work_in_progress with parameters of type NodeModifierConstructorDescriptionConstructor parameters in edu.cmu.tetrad.search.work_in_progress with type arguments of type NodeModifierConstructorDescriptionFasDci(Graph graph, IndependenceTest independenceTest, ResolveSepsets.Method method, List<Set<Node>> marginalVars, List<IndependenceTest> independenceTests, SepsetMapDci knownIndependencies, SepsetMapDci knownAssociations) Constructs a new FastAdjacencySearch for DCI with independence test pooling to resolve inconsistencies.IndTestFisherZRecursive(Matrix data, List<Node> variables, double alpha) Constructs a new Fisher Z independence test with the listed arguments.IndTestSepsetDci(SepsetMapDci sepset, List<Node> nodes) Constructs a new independence test that returns d-separation facts for the given graph as independence results. -
Uses of Node in edu.cmu.tetrad.sem
Methods in edu.cmu.tetrad.sem that return NodeModifier and TypeMethodDescriptionGeneralizedSemPm.getErrorNode(Node node) Node[]ConnectionFunction.getInputNodes()SemEvidence.getNode(int nodeIndex) SemManipulation.getNode(int nodeIndex) Parameter.getNodeA()Parameter.getNodeB()SemIm.getVariableNode(String name) Methods in edu.cmu.tetrad.sem that return types with arguments of type NodeModifier and TypeMethodDescriptionGeneralizedSemPm.getErrorNodes()Returns the list of exogenous variableNodes.StandardizedSemIm.getErrorNodes()SemPm.getLatentNodes()ReidentifyVariables.getLatents(Graph graph) DagScorer.getMeasuredNodes()GeneralizedSemPm.getMeasuredNodes()ISemIm.getMeasuredNodes()Scorer.getMeasuredNodes()SemIm.getMeasuredNodes()The list of measured nodes for the semPm.SemPm.getMeasuredNodes()StandardizedSemIm.getMeasuredNodes()The list of measured nodes for the semPm.GeneralizedSemPm.getNodes()SemEvidence.getNodesInEvidence()GeneralizedSemPm.getParents(Node node) GeneralizedSemPm.getReferencedNodes(Node node) GeneralizedSemPm.getReferencingNodes(Node node) GeneralizedSemPm.getReferencingNodes(String parameter) GeneralizedSemPm.getVariableNodes()Returns the list of variable nodes--that is, node that are not error nodes.ISemIm.getVariableNodes()LargeScaleSimulation.getVariableNodes()SemIm.getVariableNodes()The list of measured and latent nodes for the semPm.SemPm.getVariableNodes()StandardizedSemIm.getVariableNodes()DagScorer.getVariables()Scorer.getVariables()ISemIm.listUnmeasuredLatents()SemIm.listUnmeasuredLatents()Methods in edu.cmu.tetrad.sem with parameters of type NodeModifier and TypeMethodDescriptionbooleanSemIm.existsEdgeCoef(Node x, Node y) TemplateExpander.expandTemplate(String template, GeneralizedSemPm semPm, Node node) Returns the expanded template, which needs to be checked to make sure it can be used.SemPm.getCoefficientParameter(Node nodeA, Node nodeB) StandardizedSemIm.getCoefficientRange(Node a, Node b) SemPm.getCovarianceParameter(Node nodeA, Node nodeB) StandardizedSemIm.getCovarianceRange(Node a, Node b) doubleSemIm.getEdgeCoef(Node x, Node y) doubleStandardizedSemIm.getEdgeCoef(Node a, Node b) doubleSemIm.getErrCovar(Node x, Node y) doubleStandardizedSemIm.getErrorCovariance(Node a, Node b) GeneralizedSemPm.getErrorNode(Node node) doubleStandardizedSemIm.getErrorVariance(Node error) doubledoubleISemIm.getIntercept(Node node) doubleSemIm.getIntercept(Node node) doubledoubleSemPm.getMeanParameter(Node node) doubleISemIm.getMeanStdDev(Node node) doubleSemIm.getMeanStdDev(Node node) GeneralizedSemPm.getNodeExpression(Node node) GeneralizedSemPm.getNodeExpressionString(Node node) intSemEvidence.getNodeIndex(Node node) GeneralizedSemIm.getNodeSubstitutedString(Node node) GeneralizedSemIm.getNodeSubstitutedString(Node node, Map<String, Double> substitutedValues) SemPm.getParameter(Node nodeA, Node nodeB) doubleISemIm.getParamValue(Node nodeA, Node nodeB) doubleSemIm.getParamValue(Node nodeA, Node nodeB) Gets the value of a single free parameter to the given value, where the free parameter is specified by the endpoint nodes of its edge in the w graph.GeneralizedSemPm.getParents(Node node) GeneralizedSemPm.getReferencedNodes(Node node) GeneralizedSemPm.getReferencedParameters(Node node) GeneralizedSemPm.getReferencingNodes(Node node) doubledoubledoubledoubleISemIm.getVariance(Node nodeA, Matrix implCovar) doubleSemIm.getVariance(Node node, Matrix implCovar) SemPm.getVarianceParameter(Node node) 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.voidISemIm.setEdgeCoef(Node x, Node y, double value) voidSemIm.setEdgeCoef(Node x, Node y, double value) booleanStandardizedSemIm.setEdgeCoefficient(Node a, Node b, double coef) Sets the coefficient for the a->b edge to the given coefficient, if within range.voidSemIm.setErrCovar(Node x, double value) voidSemIm.setErrCovar(Node x, Node y, double value) booleanStandardizedSemIm.setErrorCovariance(Node a, Node b, double covar) Sets the covariance for the a<->b edge to the given covariance, if within range.voidvoidvoidISemIm.setIntercept(Node y, double intercept) voidSemIm.setIntercept(Node node, double intercept) Sets the intercept.voidvoidSets the mean associated with the given node.voidSemIm.setMeanStandardDeviation(Node node, double mean) Sets the mean associated with the given node.voidGeneralizedSemPm.setNodeExpression(Node node, String expressionString) voidISemIm.setParamValue(Node nodeA, Node nodeB, double value) voidSemIm.setParamValue(Node nodeA, Node nodeB, double value) Sets the value of a single free parameter to the given value, where the free parameter is specified by the endpoint nodes of its edge in the graph.voidMethod parameters in edu.cmu.tetrad.sem with type arguments of type NodeModifier and TypeMethodDescriptionSemIm.getImplCovar(List<Node> nodes) ReidentifyVariables.reidentifyVariables1(List<List<Node>> partition, Graph trueGraph) Constructors in edu.cmu.tetrad.sem with parameters of type NodeModifierConstructorDescriptionEmpiricalDistributionForExpression(GeneralizedSemPm semPm, Node error, Context context) Constructor parameters in edu.cmu.tetrad.sem with type arguments of type Node -
Uses of Node in edu.cmu.tetrad.session
Classes in edu.cmu.tetrad.session that implement NodeModifier and TypeClassDescriptionclassRepresents a node in a session for a model in a particular class.Methods in edu.cmu.tetrad.session that return NodeMethods in edu.cmu.tetrad.session with parameters of type Node -
Uses of Node in edu.cmu.tetrad.simulation
Methods in edu.cmu.tetrad.simulation that return types with arguments of type NodeModifier and TypeMethodDescriptionHsimUtils.getAllParents(Graph inputgraph, Set<Node> inputnodes) Method parameters in edu.cmu.tetrad.simulation with type arguments of type NodeModifier and TypeMethodDescriptionstatic GraphHsimUtils.getAllParents(Graph inputgraph, Set<Node> inputnodes) Constructor parameters in edu.cmu.tetrad.simulation with type arguments of type Node -
Uses of Node in edu.cmu.tetrad.study.performance
Method parameters in edu.cmu.tetrad.study.performance with type arguments of type Node -
Uses of Node in edu.cmu.tetrad.util
Methods in edu.cmu.tetrad.util that return NodeModifier and TypeMethodDescriptionstatic NodeJsonUtils.parseJSONObjectToTetradNode(org.json.JSONObject jObj) Methods in edu.cmu.tetrad.util that return types with arguments of type NodeModifier and TypeMethodDescriptionJsonUtils.parseJSONArrayToTetradNodes(org.json.JSONArray jArray) DataConvertUtils.toNodes(edu.pitt.dbmi.data.reader.DataColumn[] columns) DataConvertUtils.toNodes(edu.pitt.dbmi.data.reader.DiscreteDataColumn[] columns) -
Uses of Node in edu.pitt.csb.mgm
Methods in edu.pitt.csb.mgm that return types with arguments of type NodeMethods in edu.pitt.csb.mgm with parameters of type NodeModifier and TypeMethodDescriptionIndTestMultinomialLogisticRegressionWald.checkIndependence(Node x, Node y, Set<Node> z) booleanIndTestMultinomialLogisticRegressionWald.determines(List<Node> z, Node y) MixedUtils.getEdgeParams(Node n1, Node n2, GeneralizedSemPm pm) Method parameters in edu.pitt.csb.mgm with type arguments of type NodeModifier and TypeMethodDescriptionIndTestMultinomialLogisticRegressionWald.checkIndependence(Node x, Node y, Set<Node> z) booleanIndTestMultinomialLogisticRegressionWald.determines(List<Node> z, Node y) static int[]MixedUtils.getContinuousInds(List<Node> nodes) static int[]MixedUtils.getDiscreteInds(List<Node> nodes) IndTestMultinomialLogisticRegressionWald.indTestSubset(List<Node> vars) Constructor parameters in edu.pitt.csb.mgm with type arguments of type Node -
Uses of Node in edu.pitt.csb.stability
Method parameters in edu.pitt.csb.stability with type arguments of type NodeModifier and TypeMethodDescriptionstatic double[]StabilityUtils.totalInstabilityDir(cern.colt.matrix.DoubleMatrix2D xi, List<Node> vars) static double[]StabilityUtils.totalInstabilityUndir(cern.colt.matrix.DoubleMatrix2D xi, List<Node> vars)