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 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) Returns the variable with the given name.ConditionalGaussianBicScore.getVariable(String name) Returns the variable with the given name.DegenerateGaussianBicScore.getVariable(String name) Returns the variable with the given name.DiscreteBicScore.getVariable(String name) Returns the variable with the given name.EbicScore.getVariable(String name) Returns the variable with the given name.FisherZScore.getVariable(String name) Returns the variable with the given name.GicScores.getVariable(String name) Returns the variable with the given name.MagSemBicScore.getVariable(String name) Returns the variable with the given name.MSeparationScore.getVariable(String name) Returns the variable with the given name.MVPBicScore.getVariable(String name) Returns the variable with the given name.PoissonPriorScore.getVariable(String name) Returns the variable with the given name.PositiveCorrScore.getVariable(String name) Returns the variable with the given name.ScoreWrapper.getVariable(String name) Returns the variable with the given name.SemBicScore.getVariable(String name) Retrieves the variable with the given name from the data set.SemBicScoreDeterministic.getVariable(String name) Retrieves the Node with the given name from the data set.ZhangShenBoundScore.getVariable(String name) Retrieves the variable with the given name from the data set. -
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) existsDirectedPathFromTo. -
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) Returns the name of the given node.getNode.Evidence.getNode(int nodeIndex) getNode.MlBayesIm.getNode(int nodeIndex) Retrieves the node at the specified index.getNode.MlBayesImObs.getNode(int nodeIndex) Returns the name of the given node.getNode.UpdatedBayesIm.getNode(int nodeIndex) Returns the name of the given node.getNode.BayesPm.getVariable(Node node) Returns the variable for the given node.BayesProperties.getVariable(String targetName) Returns the variable with the given name (assumed the target).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) getCliqueTree.GraphTools.getCliqueTree(Node[] ordering, Map<Node, Set<Node>> cliques, Map<Node, Set<Node>> separators) getCliqueTree.BayesIm.getMeasuredNodes()Returns the list of measured variables.BayesPm.getMeasuredNodes()Returns the measured nodes.DirichletBayesIm.getMeasuredNodes()getMeasuredNodes.MlBayesIm.getMeasuredNodes()getMeasuredNodes.MlBayesImObs.getMeasuredNodes()getMeasuredNodes.UpdatedBayesIm.getMeasuredNodes()getMeasuredNodes.JunctionTreeAlgorithm.getNodes()getNodes.Calculate separator sets in clique tree.Calculate separator sets in clique tree.BayesIm.getVariables()Returns the list of variables.BayesImProbs.getVariables()Getter for the fieldvariables.BayesPm.getVariables()getVariables.CellTableProbs.getVariables()getVariables.DataSetProbs.getVariables()getVariables.DirichletBayesIm.getVariables()getVariables.DirichletDataSetProbs.getVariables()getVariables.IntAveDataSetProbs.getVariables()getVariables.MlBayesIm.getVariables()getVariables.MlBayesImObs.getVariables()getVariables.StoredCellProbs.getVariables()Getter for the fieldvariables.StoredCellProbsObs.getVariables()Getter for the fieldvariables.UpdatedBayesIm.getVariables()getVariables.Evidence.getVariablesInEvidence()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) getCategory.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) getCliqueTree.intBayesIm.getNodeIndex(Node node) Returns the index of the given node.intDirichletBayesIm.getNodeIndex(Node node) Returns the index of the given node.intMlBayesIm.getNodeIndex(Node node) Returns the index of the given node in the nodes array.intMlBayesImObs.getNodeIndex(Node node) Returns the index of the given node.intUpdatedBayesIm.getNodeIndex(Node node) Returns the index of the given 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) createRandomCellTable.GraphTools.getCliqueTree(Node[] ordering, Map<Node, Set<Node>> cliques, Map<Node, Set<Node>> separators) getCliqueTree.GraphTools.getCliqueTree(Node[] ordering, Map<Node, Set<Node>> cliques, Map<Node, Set<Node>> separators) getCliqueTree.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 NodeModifierConstructorDescriptionStoredCellProbsObs(List<Node> variables) Constructor for StoredCellProbsObs. -
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()getTargetNode.BoxDataSet.getVariable(int col) getVariable.BoxDataSet.getVariable(String varName) getVariable.CorrelationMatrixOnTheFly.getVariable(String name) getVariable.CovarianceMatrix.getVariable(String name) getVariable.CovarianceMatrixOnTheFly.getVariable(String name) getVariable.DataModel.getVariable(String name) getVariable.DataModelList.getVariable(String name) getVariable.DataSet.getVariable(int column) getVariable.DataSet.getVariable(String name) getVariable.ICovarianceMatrix.getVariable(String name) getVariable.IndependenceFacts.getVariable(String name) getVariable.NumberObjectDataSet.getVariable(int col) getVariable.NumberObjectDataSet.getVariable(String varName) getVariable.TimeSeriesData.getVariable(String name) getVariable.abstract NodeCreates a new node of the same type as this one with the given name.Creates a new node of the same type as this one with the given name.Creates a new node of the same type as this one with the given name.Methods in edu.cmu.tetrad.data that return types with arguments of type NodeModifier and TypeMethodDescriptionDataUtils.createContinuousVariables(String[] varNames) createContinuousVariables.DataTransforms.getConstantColumns(DataSet dataSet) getConstantColumns.DataUtils.getExampleNonsingular(ICovarianceMatrix covarianceMatrix, int depth) getExampleNonsingular.NumberObjectDataSet.getSelectedVariables()getSelectedVariables.BoxDataSet.getVariables()Getter for the fieldvariables.CorrelationMatrixOnTheFly.getVariables()Getter for the fieldvariables.CovarianceMatrix.getVariables()Getter for the fieldvariables.CovarianceMatrixOnTheFly.getVariables()Getter for the fieldvariables.DataModelList.getVariables()getVariables.DataSet.getVariables()getVariables.ICovarianceMatrix.getVariables()getVariables.IndependenceFacts.getVariables()getVariables.NumberObjectDataSet.getVariables()Getter for the fieldvariables.TimeSeriesData.getVariables()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 at the given index.voidBoxDataSet.addVariable(Node variable) Adds the given variable to the data set.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) addVariable.voidNumberObjectDataSet.addVariable(int index, Node variable) Adds the given variable at the given index.voidNumberObjectDataSet.addVariable(Node variable) Adds the given variable to the data set.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) copyColumn.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.intgetColumn.intgetColumn.intgetColumn.booleanIndependenceFacts.isIndependent(Node x, Node y, Node... z) isIndependent.booleanIndependenceFacts.isIndependent(Node x, Node y, Set<Node> z) isIndependent.intKnowledge.isInWhichTier(Node node) Returns the index of the tier of node if it's in a tier, otherwise -1.booleanBoxDataSet.isSelected(Node variable) isSelected.final booleanCorrelationMatrixOnTheFly.isSelected(Node variable) isSelected.final booleanCovarianceMatrix.isSelected(Node variable) isSelected.final booleanCovarianceMatrixOnTheFly.isSelected(Node variable) isSelected.booleanDataSet.isSelected(Node variable) isSelected.booleanICovarianceMatrix.isSelected(Node variable) isSelected.booleanNumberObjectDataSet.isSelected(Node variable) isSelected.voidBoxDataSet.removeColumn(Node variable) Removes the given variable, along with all of its data.voidDataSet.removeColumn(Node variable) Removes the given variable, along with all of its data.voidNumberObjectDataSet.removeColumn(Node variable) Removes the given variable, along with all of its data.final voidselect.final voidselect.final voidselect.voidselect.voidBoxDataSet.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 MatrixsubMatrix.static MatrixsubMatrix.static MatrixsubMatrix.static MatrixsubMatrix.Method parameters in edu.cmu.tetrad.data with type arguments of type NodeModifier and TypeMethodDescriptionbooleanIndependenceFacts.isIndependent(Node x, Node y, Set<Node> z) isIndependent.voidSetter for the fieldnodes.voidCorrelationMatrixOnTheFly.setVariables(List<Node> variables) setVariables.voidCovarianceMatrix.setVariables(List<Node> variables) setVariables.voidCovarianceMatrixOnTheFly.setVariables(List<Node> variables) setVariables.voidICovarianceMatrix.setVariables(List<Node> variables) setVariables.static MatrixsubMatrix.static MatrixsubMatrix.static MatrixsubMatrix.static MatrixsubMatrix.static MatrixsubMatrix.static MatrixsubMatrix.BoxDataSet.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) Constructs a new data set with the given number of rows and columns, with all values set to missing.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) Constructor for CovarianceMatrix.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) Constructor for Discretizer.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) Constructor for NumberObjectDataSet. -
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) Returns the associated node for the given error node in the specified 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) getErrorNode.SemGraph.getExogenous(Node node) getExogenous.NodePair.getFirst()Getter for the fieldfirst.Retrieves the node in the graph with the specified name.getNode.getNode.getNode.getNode.Retrieves a Node from the graph based on the given name.getNode.final NodeEdge.getNode1()Getter for the fieldnode1.final NodeEdge.getNode2()Getter for the fieldnode2.NodePair.getSecond()Getter for the fieldsecond.static NodeGraphUtils.getTrekSource(Graph graph, List<Node> trek) This method returns the source node of a given trek in a graph.SemGraph.getVarNode(Node node) getVarNode.IndependenceFact.getX()Getter for the fieldx.Triple.getX()Getter for the fieldx.IndependenceFact.getY()Getter for the fieldy.Triple.getY()Getter for the fieldy.Triple.getZ()Getter for the fieldz.Creates a new node of the same type as this one with the given name.Creates a new node of the same type as this one with the given name.static NodeIf node is one endpoint of edge, returns the other endpoint.static 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) Traverses a semi-directed edge to identify the next node in the traversal.Methods in edu.cmu.tetrad.graph that return types with arguments of type NodeModifier and TypeMethodDescriptionPaths.allDirectedPaths(Node node1, Node node2, int maxLength) Finds all directed paths from node1 to node2 with a maximum length.Finds all paths from node1 to node2 within a specified maximum length.GraphUtils.anteriority(Graph G, Node... x) Computes the anteriority of the given nodes in a graph.Paths.anteriority(Node... X) Returns the set of nodes that are in the anteriority of the given nodes in the graph.Constructs a list of nodes from the givennodeslist at the given indices in that list.Converts an array of indices into a set of corresponding nodes from a given list of nodes.Converts the given array of nodes into a Set of nodes.Paths.connectedComponents()Returns a list of connected components in the graph.Paths.directedPaths(Node node1, Node node2, int maxLength) Finds all directed paths from node1 to node2 with a maximum length.Calculates the district of a given node in a graph.Dag.getAdjacentNodes(Node node) Retrieves the adjacent nodes of a given node in the graph.EdgeListGraph.getAdjacentNodes(Node node) getAdjacentNodes.Graph.getAdjacentNodes(Node node) getAdjacentNodes.LagGraph.getAdjacentNodes(Node node) getAdjacentNodes.SemGraph.getAdjacentNodes(Node node) getAdjacentNodes.TimeLagGraph.getAdjacentNodes(Node node) Retrieves a list of adjacent nodes for the given 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(Node node) Retrieves the ancestors of a specified `Node` in the graph.Paths.getAncestors(List<Node> nodes) Returns a list of all ancestors of the given nodes.Dag.getChildren(Node node) Retrieves the children of a specified Node in the graph.EdgeListGraph.getChildren(Node node) getChildren.Graph.getChildren(Node node) getChildren.LagGraph.getChildren(Node node) getChildren.SemGraph.getChildren(Node node) getChildren.TimeLagGraph.getChildren(Node node) Returns a list of children nodes for the given node.Paths.getDescendants(Node node) Returns a list of all descendants of the given node.Paths.getDescendants(List<Node> nodes) Retrieves the descendants of the given list of nodes.SemGraph.getFullTierOrdering()getFullTierOrdering.Paths.getInducingPath(Node x, Node y) This method calculates the inducing path between two measured nodes in a graph.TimeLagGraph.getLag0Nodes()Getter for the fieldlag0Nodes.Paths.getMConnectedVars(Node y, Set<Node> z) Retrieves the set of nodes that are connected to the given nodeyand are also present in the set of nodesz.getMConnectedVars.Dag.getNodes()getNodes.EdgeListGraph.getNodes()getNodes.Graph.getNodes()getNodes.LagGraph.getNodes()getNodes.SemGraph.getNodes()getNodes.TimeLagGraph.getNodes()Retrieves a list of nodes from the graph.Dag.getNodesInTo(Node node, Endpoint n) Retrieves a list of nodes in the given graph that have edges pointing into the specified node and endpoint.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) Nodes adjacent to the given node with the given proximal endpoint.SemGraph.getNodesInTo(Node node, Endpoint endpoint) Nodes adjacent to the given node with the given proximal endpoint.TimeLagGraph.getNodesInTo(Node node, Endpoint endpoint) Retrieves a list of nodes that have an incoming edge from a specific node and endpoint.Dag.getNodesOutTo(Node node, Endpoint n) Retrieves a list of nodes that have outgoing edges to a specified node and endpoint.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) Nodes adjacent to the given node with the given distal endpoint.SemGraph.getNodesOutTo(Node node, Endpoint n) Nodes adjacent to the given node with the given distal endpoint.TimeLagGraph.getNodesOutTo(Node node, Endpoint endpoint) Retrieves the list of nodes in a graph that have an outgoing edge to the given node and endpoint.Dag.getParents(Node node) Retrieves the list of parent nodes for a given node in the graph.EdgeListGraph.getParents(Node node) getParents.Graph.getParents(Node node) getParents.LagGraph.getParents(Node node) getParents.Paths.getParents(List<Node> pi, int p, Graph g, boolean verbose, boolean allowSelectionBias) Returns the parents of the node at index p, calculated using Pearl's method.SemGraph.getParents(Node node) getParents.TimeLagGraph.getParents(Node node) Returns the list of parent nodes for the given node.Returns the sepset between two given nodes in the graph.getSepset.getSepset.getSepset.getSepset.getSepset.Retrieves the sepset of two nodes in the graph.Paths.getValidOrder(List<Node> initialOrder, boolean forward) Returns a valid causal order for either a DAG or a CPDAG.IndependenceFact.getZ()getZ.GraphUtils.markovBlanket(Node x, Graph G) Returns a Markov blanket of a node for a DAG, CPDAG, MAG, or PAG.Paths.maxCliques()Returns a set of all maximum cliques in the graph.GraphUtils.maximalCliques(Graph graph, List<Node> nodes) Finds all maximal cliques in a given graph.Paths.possibleMsep(Node x, Node y, int maxPathLength) possibleMsep.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.semidirectedPaths(Node node1, Node node2, int maxLength) Finds all semi-directed paths between two nodes up to a maximum length.Finds all treks from node1 to node2 with a maximum length.Paths.treksIncludingBidirected(Node node1, Node node2) Finds all possible treks between two nodes, including bidirectional treks.GraphUtils.visibleEdgeAdjustments1(Graph G, Node x, Node y, int numSmallestSizes, GraphUtils.GraphType graphType) Calculates visual-edge adjustments given graph G between two nodes x and y that are subsets of MB(X).GraphUtils.visibleEdgeAdjustments3(Graph G, Node x, Node y, int numSmallestSizes, GraphUtils.GraphType graphType) This method calculates visible-edge adjustments for a given graph, two nodes, a number of smallest sizes, and a graph type.GraphUtils.visualEdgeAdjustments2(Graph G, Node x, Node y, int numSmallestSizes, GraphUtils.GraphType graphType) Calculates visual-edge adjustments of a given graph G between two nodes x and y that are subsets of MB(Y).Methods in edu.cmu.tetrad.graph with parameters of type NodeModifier and TypeMethodDescriptionvoidDag.addAmbiguousTriple(Node x, Node y, Node z) Adds an ambiguous triple to the list of ambiguous triples.voidEdgeListGraph.addAmbiguousTriple(Node x, Node y, Node z) addAmbiguousTriple.voidGraph.addAmbiguousTriple(Node x, Node y, Node z) addAmbiguousTriple.voidLagGraph.addAmbiguousTriple(Node x, Node y, Node z) addAmbiguousTriple.voidSemGraph.addAmbiguousTriple(Node x, Node y, Node z) addAmbiguousTriple.voidTimeLagGraph.addAmbiguousTriple(Node x, Node y, Node z) Adds an ambiguous triple to the list of ambiguous triples.voidUnderlines.addAmbiguousTriple(Node x, Node y, Node z) addAmbiguousTriple.booleanDag.addBidirectedEdge(Node node1, Node node2) Adds a bidirectional edge between two nodes.booleanEdgeListGraph.addBidirectedEdge(Node node1, Node node2) Adds a bidirected edges <-> to the graph.booleanGraph.addBidirectedEdge(Node node1, Node node2) Adds a bidirected edges <-> to the graph.booleanLagGraph.addBidirectedEdge(Node node1, Node node2) Adds a bidirected edges <-> to the graph.booleanSemGraph.addBidirectedEdge(Node nodeA, Node nodeB) Adds a bidirected edges <-> to the graph.booleanTimeLagGraph.addBidirectedEdge(Node node1, Node node2) Adds a bidirected edge between two nodes.booleanDag.addDirectedEdge(Node node1, Node node2) Adds a directed edge between two nodes.booleanEdgeListGraph.addDirectedEdge(Node node1, Node node2) Adds a directed edge --> to the graph.booleanGraph.addDirectedEdge(Node node1, Node node2) Adds a directed edge --> to the graph.booleanLagGraph.addDirectedEdge(Node node1, Node node2) Adds a directed edge --> to the graph.booleanSemGraph.addDirectedEdge(Node nodeA, Node nodeB) Adds a directed edge --> to the graph.booleanTimeLagGraph.addDirectedEdge(Node node1, Node node2) Adds a directed edge between two nodes to the graph.voidDag.addDottedUnderlineTriple(Node x, Node y, Node z) Adds a dotted underline triple to the graph.voidEdgeListGraph.addDottedUnderlineTriple(Node x, Node y, Node z) addDottedUnderlineTriple.voidGraph.addDottedUnderlineTriple(Node x, Node y, Node z) addDottedUnderlineTriple.voidLagGraph.addDottedUnderlineTriple(Node x, Node y, Node z) addDottedUnderlineTriple.voidSemGraph.addDottedUnderlineTriple(Node x, Node y, Node z) addDottedUnderlineTriple.voidTimeLagGraph.addDottedUnderlineTriple(Node x, Node y, Node z) Adds a triple with dotted underline to the list of triples.voidUnderlines.addDottedUnderlineTriple(Node x, Node y, Node z) addDottedUnderlineTriple.booleanAdds a Node to the graph.booleanAdds a node to the graph.booleanAdds a node to the graph.booleanAdds a node to the graph.booleanAdds a node to the graph.booleanAdds a node to the graph.booleanDag.addNondirectedEdge(Node node1, Node node2) Adds a nondirected edge between two nodes in the graph.booleanEdgeListGraph.addNondirectedEdge(Node node1, Node node2) Adds a nondirected edges o-o to the graph.booleanGraph.addNondirectedEdge(Node node1, Node node2) Adds a nondirected edges o-o to the graph.booleanLagGraph.addNondirectedEdge(Node node1, Node node2) Adds a nondirected edges o-o to the graph.booleanSemGraph.addNondirectedEdge(Node nodeA, Node nodeB) Adds a nondirected edges o-o to the graph.booleanTimeLagGraph.addNondirectedEdge(Node node1, Node node2) Adds a nondirected edge between two nodes.booleanDag.addPartiallyOrientedEdge(Node node1, Node node2) Adds a partially oriented edge between two nodes.booleanEdgeListGraph.addPartiallyOrientedEdge(Node node1, Node node2) Adds a partially oriented edge o-> to the graph.booleanGraph.addPartiallyOrientedEdge(Node node1, Node node2) Adds a partially oriented edge o-> to the graph.booleanLagGraph.addPartiallyOrientedEdge(Node node1, Node node2) Adds a partially oriented edge o-> to the graph.booleanSemGraph.addPartiallyOrientedEdge(Node nodeA, Node nodeB) Adds a partially oriented edge o-> to the graph.booleanTimeLagGraph.addPartiallyOrientedEdge(Node node1, Node node2) Adds a partially oriented edge between two given nodes.voidDag.addUnderlineTriple(Node x, Node y, Node z) Adds an underline triple to the current object.voidEdgeListGraph.addUnderlineTriple(Node x, Node y, Node z) addUnderlineTriple.voidGraph.addUnderlineTriple(Node x, Node y, Node z) addUnderlineTriple.voidLagGraph.addUnderlineTriple(Node x, Node y, Node z) addUnderlineTriple.voidSemGraph.addUnderlineTriple(Node x, Node y, Node z) addUnderlineTriple.voidTimeLagGraph.addUnderlineTriple(Node x, Node y, Node z) Adds an underline triple consisting of three nodes to the graph.voidUnderlines.addUnderlineTriple(Node x, Node y, Node z) addUnderlineTriple.booleanDag.addUndirectedEdge(Node node1, Node node2) Adds an undirected edge between two nodes.booleanEdgeListGraph.addUndirectedEdge(Node node1, Node node2) Adds an undirected edge --- to the graph.booleanGraph.addUndirectedEdge(Node node1, Node node2) Adds an undirected edge --- to the graph.booleanLagGraph.addUndirectedEdge(Node node1, Node node2) Adds an undirected edge --- to the graph.booleanSemGraph.addUndirectedEdge(Node nodeA, Node nodeB) Adds an undirected edge --- to the graph.booleanTimeLagGraph.addUndirectedEdge(Node node1, Node node2) Adds an undirected edge between two nodes.Paths.allDirectedPaths(Node node1, Node node2, int maxLength) Finds all directed paths from node1 to node2 with a maximum length.Finds all paths from node1 to node2 within a specified maximum length.GraphUtils.anteriority(Graph G, Node... x) Computes the anteriority of the given nodes in a graph.Paths.anteriority(Node... X) Returns the set of nodes that are in the anteriority of the given nodes in the graph.Converts the given array of nodes into a Set of nodes.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) Checks if the given Node object is contained in the graph.booleanEdgeListGraph.containsNode(Node node) Determines whether this graph contains the given node.booleanGraph.containsNode(Node node) Determines whether this graph contains the given node.booleanLagGraph.containsNode(Node node) Determines whether this graph contains the given node.booleanSemGraph.containsNode(Node node) Determines whether this graph contains the given node.booleanTimeLagGraph.containsNode(Node node) Checks if the graph contains a specific 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.directedPaths(Node node1, Node node2, int maxLength) Finds all directed paths from node1 to node2 with a maximum length.Calculates the district of a given node in a graph.booleanPaths.existsDirectedPath(Node node1, Node node2) Checks if a directed path exists between two nodes in a graph.booleanPaths.existsDirectedPath(Node node1, Node node2, int depth) Checks if a directed path exists between two nodes within a certain 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) existsInducingPathVisit.booleanPaths.existsSemiDirectedPath(Node from, Node to) existsSemiDirectedPath.booleanPaths.existsSemiDirectedPath(Node node1, Set<Node> nodes) existsSemiDirectedPath.booleanPaths.existsTrek(Node node1, Node node2) Determines whether a trek exists between two nodes in the graph.Dag.getAdjacentNodes(Node node) Retrieves the adjacent nodes of a given node in the graph.EdgeListGraph.getAdjacentNodes(Node node) getAdjacentNodes.Graph.getAdjacentNodes(Node node) getAdjacentNodes.LagGraph.getAdjacentNodes(Node node) getAdjacentNodes.SemGraph.getAdjacentNodes(Node node) getAdjacentNodes.TimeLagGraph.getAdjacentNodes(Node node) Retrieves a list of adjacent nodes for the given node.GraphUtils.getAmbiguousTriplesFromGraph(Node node, Graph graph) Retrieves the list of ambiguous triples from the given graph for a given node.Paths.getAncestors(Node node) Retrieves the ancestors of a specified `Node` in the graph.static NodeGraphUtils.getAssociatedNode(Node errorNode, Graph graph) Returns the associated node for the given error node in the specified graph.Dag.getChildren(Node node) Retrieves the children of a specified Node in the graph.EdgeListGraph.getChildren(Node node) getChildren.Graph.getChildren(Node node) getChildren.LagGraph.getChildren(Node node) getChildren.SemGraph.getChildren(Node node) getChildren.TimeLagGraph.getChildren(Node node) Returns a list of children nodes for the given node.GraphSaveLoadUtils.getCollidersFromGraph(Node node, Graph graph) getCollidersFromGraph.intReturns the degree of a given node in the graph.intgetDegree.intgetDegree.intgetDegree.intgetDegree.intRetrieves the degree of a given node in the graph.Paths.getDescendants(Node node) Returns a list of all descendants of the given node.Dag.getDirectedEdge(Node node1, Node node2) Returns the directed edge between the given nodes, if one exists in the graph.EdgeListGraph.getDirectedEdge(Node node1, Node node2) getDirectedEdge.Graph.getDirectedEdge(Node node1, Node node2) getDirectedEdge.LagGraph.getDirectedEdge(Node node1, Node node2) getDirectedEdge.SemGraph.getDirectedEdge(Node node1, Node node2) getDirectedEdge.TimeLagGraph.getDirectedEdge(Node node1, Node node2) Retrieves the directed edge connecting two nodes in the graph.final EndpointEdge.getDistalEndpoint(Node node) getDistalEndpoint.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) Retrieves the list of dotted and underlined triples from the given graph, with the specified node as the middle node.Retrieves the edge between two nodes in the graph.getEdge.getEdge.getEdge.getEdge.Retrieves the edge between the given nodes.Returns a list of edges connected to the given node.Returns a list of edges between the specified nodes in the graph.getEdges.getEdges.getEdges.getEdges.getEdges.getEdges.getEdges.getEdges.Returns the list of edges connected to the specified node.Finds all edges between two nodes.Dag.getEndpoint(Node node1, Node node2) Returns the endpoint between two nodes in the graph.EdgeListGraph.getEndpoint(Node node1, Node node2) getEndpoint.Graph.getEndpoint(Node node1, Node node2) getEndpoint.LagGraph.getEndpoint(Node node1, Node node2) getEndpoint.SemGraph.getEndpoint(Node node1, Node node2) getEndpoint.TimeLagGraph.getEndpoint(Node node1, Node node2) Returns the endpoint between two nodes in the graph.SemGraph.getErrorNode(Node node) getErrorNode.SemGraph.getExogenous(Node node) getExogenous.static GraphGraphUtils.getGraphWithoutXToY(Graph G, Node x, Node y, GraphUtils.GraphType graphType) Returns a graph that is obtained by removing the edge from node x to node y from the input graph.intDag.getIndegree(Node node) Returns the indegree of the specified node in the graph.intEdgeListGraph.getIndegree(Node node) getIndegree.intGraph.getIndegree(Node node) getIndegree.intLagGraph.getIndegree(Node node) getIndegree.intSemGraph.getIndegree(Node node) getIndegree.intTimeLagGraph.getIndegree(Node node) Returns the indegree of a given node in the graph.Paths.getInducingPath(Node x, Node y) This method calculates the inducing path between two measured nodes in a graph.static GraphGraphUtils.getMarkovBlanketSubgraphWithTargetNode(Graph graph, Node target) Calculates the subgraph over the Markov blanket of a target node for a DAG, CPDAG, MAG, or PAG.Paths.getMConnectedVars(Node y, Set<Node> z) Retrieves the set of nodes that are connected to the given nodeyand are also present in the set of nodesz.getMConnectedVars.getNodeId.Dag.getNodesInTo(Node node, Endpoint n) Retrieves a list of nodes in the given graph that have edges pointing into the specified node and endpoint.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) Nodes adjacent to the given node with the given proximal endpoint.SemGraph.getNodesInTo(Node node, Endpoint endpoint) Nodes adjacent to the given node with the given proximal endpoint.TimeLagGraph.getNodesInTo(Node node, Endpoint endpoint) Retrieves a list of nodes that have an incoming edge from a specific node and endpoint.Dag.getNodesOutTo(Node node, Endpoint n) Retrieves a list of nodes that have outgoing edges to a specified node and endpoint.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) Nodes adjacent to the given node with the given distal endpoint.SemGraph.getNodesOutTo(Node node, Endpoint n) Nodes adjacent to the given node with the given distal endpoint.TimeLagGraph.getNodesOutTo(Node node, Endpoint endpoint) Retrieves the list of nodes in a graph that have an outgoing edge to the given node and endpoint.intDag.getNumEdges(Node node) Returns the number of edges connected to the specified node.intEdgeListGraph.getNumEdges(Node node) getNumEdges.intGraph.getNumEdges(Node node) getNumEdges.intLagGraph.getNumEdges(Node node) getNumEdges.intSemGraph.getNumEdges(Node node) getNumEdges.intTimeLagGraph.getNumEdges(Node node) Retrieves the number of edges connected to a specific node.intDag.getOutdegree(Node node) Returns the outdegree of the given node.intEdgeListGraph.getOutdegree(Node node) getOutdegree.intGraph.getOutdegree(Node node) getOutdegree.intLagGraph.getOutdegree(Node node) getOutdegree.intSemGraph.getOutdegree(Node node) getOutdegree.intTimeLagGraph.getOutdegree(Node node) Retrieves the outdegree of the specified node in the graph.Dag.getParents(Node node) Retrieves the list of parent nodes for a given node in the graph.EdgeListGraph.getParents(Node node) getParents.Graph.getParents(Node node) getParents.LagGraph.getParents(Node node) getParents.SemGraph.getParents(Node node) getParents.TimeLagGraph.getParents(Node node) Returns the list of parent nodes for the given node.final EndpointEdge.getProximalEndpoint(Node node) getProximalEndpoint.Returns the sepset between two given nodes in the graph.getSepset.getSepset.getSepset.getSepset.getSepset.Retrieves the sepset of two nodes in the graph.EdgeListGraph.getTriplesLists(Node node) getTriplesLists.TripleClassifier.getTriplesLists(Node node) getTriplesLists.Underlines.getTriplesLists(Node node) getTriplesLists.GraphUtils.getUnderlinedTriplesFromGraph(Node node, Graph graph) Retrieves the underlined triples from the given graph that involve the specified node.SemGraph.getVarNode(Node node) getVarNode.booleanDag.isAdjacentTo(Node node1, Node node2) Determines whether two nodes are adjacent in the graph.booleanEdgeListGraph.isAdjacentTo(Node node1, Node node2) isAdjacentTo.booleanGraph.isAdjacentTo(Node node1, Node node2) isAdjacentTo.booleanLagGraph.isAdjacentTo(Node node1, Node node2) isAdjacentTo.booleanSemGraph.isAdjacentTo(Node nodeX, Node nodeY) isAdjacentTo.booleanTimeLagGraph.isAdjacentTo(Node node1, Node node2) Determines whether two nodes are adjacent in the graph.booleanDag.isAmbiguousTriple(Node x, Node y, Node z) Determines if a triple of nodes is ambiguous.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) Checks whether a triple of nodes is ambiguous.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) isAncestorOf.booleanPaths.isAncestorOf(Node node1, Node node2) Determines whether one node is an ancestor of another.booleanChecks if the given node1 is a child of node2 in the graph.booleanisChildOf.booleanisChildOf.booleanisChildOf.booleanisChildOf.booleanChecks if a given node is a child of another node in the graph.static booleanChecks if the given trek in a graph is a confounding trek.booleanDag.isDefCollider(Node node1, Node node2, Node node3) Checks if there is a definite collider between three nodes in the graph.booleanEdgeListGraph.isDefCollider(Node node1, Node node2, Node node3) Added by ekorber, 2004/6/9.booleanGraph.isDefCollider(Node node1, Node node2, Node node3) Added by ekorber, 2004/6/9.booleanLagGraph.isDefCollider(Node node1, Node node2, Node node3) Added by ekorber, 2004/6/9.booleanSemGraph.isDefCollider(Node node1, Node node2, Node node3) Added by ekorber, 2004/6/9.booleanTimeLagGraph.isDefCollider(Node node1, Node node2, Node node3) Determines if there is a definite collider relationship between the given nodes.booleanDag.isDefNoncollider(Node node1, Node node2, Node node3) Checks if three given nodes form a definite non-collider in a graph.booleanEdgeListGraph.isDefNoncollider(Node node1, Node node2, Node node3) Added by ekorber, 2004/6/9.booleanGraph.isDefNoncollider(Node node1, Node node2, Node node3) Added by ekorber, 2004/6/9.booleanLagGraph.isDefNoncollider(Node node1, Node node2, Node node3) Added by ekorber, 2004/6/9.booleanSemGraph.isDefNoncollider(Node node1, Node node2, Node node3) Added by ekorber, 2004/6/9.booleanTimeLagGraph.isDefNoncollider(Node node1, Node node2, Node node3) Determines if the given nodes form a definite noncollider in the graph.booleanPaths.isDescendentOf(Node node1, Node node2) Determines whether one node is a descendent of another.booleanPaths.isDirected(Node node1, Node node2) Checks if there is a directed edge from node1 to node2 in the graph.booleanDag.isExogenous(Node node) Checks whether a given node is exogenous.booleanEdgeListGraph.isExogenous(Node node) isExogenous.booleanGraph.isExogenous(Node node) isExogenous.booleanLagGraph.isExogenous(Node node) isExogenous.booleanSemGraph.isExogenous(Node node) isExogenous.booleanTimeLagGraph.isExogenous(Node node) Checks if a given node is exogenous.booleanPaths.isMConnectedTo(Node x, Node y, Set<Node> z, boolean allowSelectionBias) Detemrmines whether x and y are d-connected given z.booleanPaths.isMConnectedTo(Node x, Node y, Set<Node> z, Map<Node, Set<Node>> ancestors, boolean allowSelectionBias) Detemrmines 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, boolean allowSelectionBias) Determines whether one n ode is d-separated from another.booleanPaths.isMSeparatedFrom(Node node1, Node node2, Set<Node> z, Map<Node, Set<Node>> ancestors, boolean allowSelectionBias) Checks if two nodes are M-separated.booleanDag.isParameterizable(Node node) Checks if the given node is parameterizable.booleanEdgeListGraph.isParameterizable(Node node) isParameterizable.booleanGraph.isParameterizable(Node node) isParameterizable.booleanLagGraph.isParameterizable(Node node) isParameterizable.booleanSemGraph.isParameterizable(Node node) isParameterizable.booleanTimeLagGraph.isParameterizable(Node node) Checks if a node is parameterizable.booleanDag.isParentOf(Node node1, Node node2) Determines if a given node is a parent of another node in the graph.booleanEdgeListGraph.isParentOf(Node node1, Node node2) Determines whether node1 is a parent of node2.booleanGraph.isParentOf(Node node1, Node node2) Determines whether node1 is a parent of node2.booleanLagGraph.isParentOf(Node node1, Node node2) Determines whether node1 is a parent of node2.booleanSemGraph.isParentOf(Node node1, Node node2) Determines whether node1 is a parent of node2.booleanTimeLagGraph.isParentOf(Node node1, Node node2) Determines if a given node is a parent of another node in the graph.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) Determines if a triple of nodes is underlined.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) Checks whether a given triple (x, y, z) is an underline triple.booleanUnderlines.isUnderlineTriple(Node x, Node y, Node z) States whether r-s-r is an underline triple or not.booleanPaths.isUndirected(Node node1, Node node2) Checks if the edge between two nodes in the graph is undirected.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) pathString.static StringTriple.pathString(Graph graph, Node x, Node y, Node z) pathString.booleanEdge.pointsTowards(Node node) pointsTowards.booleanPaths.possibleAncestor(Node node1, Node node2) possibleAncestor.Paths.possibleMsep(Node x, Node y, int maxPathLength) possibleMsep.voidDag.removeAmbiguousTriple(Node x, Node y, Node z) Removes an ambiguous triple from the list of ambiguous triples.voidEdgeListGraph.removeAmbiguousTriple(Node x, Node y, Node z) removeAmbiguousTriple.voidGraph.removeAmbiguousTriple(Node x, Node y, Node z) removeAmbiguousTriple.voidLagGraph.removeAmbiguousTriple(Node x, Node y, Node z) removeAmbiguousTriple.voidSemGraph.removeAmbiguousTriple(Node x, Node y, Node z) removeAmbiguousTriple.voidTimeLagGraph.removeAmbiguousTriple(Node x, Node y, Node z) Removes an ambiguous triple from the collection.voidUnderlines.removeAmbiguousTriple(Node x, Node y, Node z) removeAmbiguousTriple.voidDag.removeDottedUnderlineTriple(Node x, Node y, Node z) Removes a dotted underline triple from the set of triples.voidEdgeListGraph.removeDottedUnderlineTriple(Node x, Node y, Node z) removeDottedUnderlineTriple.voidGraph.removeDottedUnderlineTriple(Node x, Node y, Node z) removeDottedUnderlineTriple.voidLagGraph.removeDottedUnderlineTriple(Node x, Node y, Node z) removeDottedUnderlineTriple.voidSemGraph.removeDottedUnderlineTriple(Node x, Node y, Node z) removeDottedUnderlineTriple.voidTimeLagGraph.removeDottedUnderlineTriple(Node x, Node y, Node z) Removes a triple of nodes from the set of dottedUnderLineTriples.voidUnderlines.removeDottedUnderlineTriple(Node x, Node y, Node z) removeDottedUnderlineTriple.booleanDag.removeEdge(Node node1, Node node2) Removes the edge between two nodes in the graph.booleanEdgeListGraph.removeEdge(Node node1, Node node2) Removes the edge connecting the two given nodes, provided there is exactly one such edge.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) Removes the edge connecting the two given nodes, provided there is exactly one such edge.booleanSemGraph.removeEdge(Node node1, Node node2) Removes the edge connecting the two given nodes, provided there is exactly one such edge.booleanTimeLagGraph.removeEdge(Node node1, Node node2) Removes the edge between two given nodes.booleanDag.removeEdges(Node node1, Node node2) Removes an edge between two nodes.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) Removes all edges connecting node A to node B.booleanSemGraph.removeEdges(Node node1, Node node2) Removes all edges connecting node A to node B.booleanTimeLagGraph.removeEdges(Node node1, Node node2) Removes edges between two nodes.booleanDag.removeNode(Node node) Removes the specified node from the graph.booleanEdgeListGraph.removeNode(Node node) Removes a node from the graph.booleanGraph.removeNode(Node node) Removes a node from the graph.booleanLagGraph.removeNode(Node node) Removes a node from the graph.booleanSemGraph.removeNode(Node node) Removes a node from the graph.booleanTimeLagGraph.removeNode(Node node) Removes the given node from the graph.voidDag.removeUnderlineTriple(Node x, Node y, Node z) Removes an underline triple from the list of underline triples.voidEdgeListGraph.removeUnderlineTriple(Node x, Node y, Node z) removeUnderlineTriple.voidGraph.removeUnderlineTriple(Node x, Node y, Node z) removeUnderlineTriple.voidLagGraph.removeUnderlineTriple(Node x, Node y, Node z) removeUnderlineTriple.voidSemGraph.removeUnderlineTriple(Node x, Node y, Node z) removeUnderlineTriple.voidTimeLagGraph.removeUnderlineTriple(Node x, Node y, Node z) Removes the specified triple (x, y, z) from the list of underline triples.voidUnderlines.removeUnderlineTriple(Node x, Node y, Node z) removeUnderlineTriple.Paths.semidirectedPaths(Node node1, Node node2, int maxLength) Finds all semi-directed paths between two nodes up to a maximum length.booleanDag.setEndpoint(Node from, Node to, Endpoint endPoint) Sets the endpoint of a directed edge between two nodes in a graph.booleanEdgeListGraph.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.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) Sets the endpoint type at the 'to' end of the edge from 'from' to 'to' to the given endpoint.booleanSemGraph.setEndpoint(Node node1, Node node2, Endpoint endpoint) Sets the endpoint type at the 'to' end of the edge from 'from' to 'to' to the given endpoint.booleanTimeLagGraph.setEndpoint(Node from, Node to, Endpoint endPoint) Sets the endpoint of an edge between two nodes in the graph.static NodeIf node is one endpoint of edge, returns the other endpoint.static 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) Traverses a semi-directed edge to identify the next node in the traversal.Finds all treks from node1 to node2 with a maximum length.Paths.treksIncludingBidirected(Node node1, Node node2) Finds all possible treks between two nodes, including bidirectional treks.static EdgeEdges.undirectedEdge(Node nodeA, Node nodeB) Constructs a new undirected edge from nodeA to nodeB (--).GraphUtils.visibleEdgeAdjustments1(Graph G, Node x, Node y, int numSmallestSizes, GraphUtils.GraphType graphType) Calculates visual-edge adjustments given graph G between two nodes x and y that are subsets of MB(X).GraphUtils.visibleEdgeAdjustments3(Graph G, Node x, Node y, int numSmallestSizes, GraphUtils.GraphType graphType) This method calculates visible-edge adjustments for a given graph, two nodes, a number of smallest sizes, and a graph type.GraphUtils.visualEdgeAdjustments2(Graph G, Node x, Node y, int numSmallestSizes, GraphUtils.GraphType graphType) Calculates visual-edge adjustments of a given graph G between two nodes x and y that are subsets of MB(Y).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.Converts an array of indices into a set of corresponding nodes from a given list of nodes.MisclassificationUtils.convertNodes(Set<Edge> edges, List<Node> newVariables) convertNodes.booleanPaths.existsInducingPathVisit(Node a, Node b, Node x, Node y, LinkedList<Node> path) existsInducingPathVisit.booleanPaths.existsSemiDirectedPath(Node node1, Set<Node> nodes) existsSemiDirectedPath.static voidGraphUtils.fciOrientbk(Knowledge knowledge, Graph graph, List<Node> variables) Attempts to orient the edges in the graph based on the given knowledge.Paths.getAncestors(List<Node> nodes) Returns a list of all ancestors of the given nodes.static GraphGenerates a directed acyclic graph (DAG) based on the given list of nodes using Raskutti and Uhler's method.Returns the parent matrix for the graph.Paths.getDescendants(List<Node> nodes) Retrieves the descendants of the given list of nodes.Paths.getMConnectedVars(Node y, Set<Node> z) Retrieves the set of nodes that are connected to the given nodeyand are also present in the set of nodesz.getMConnectedVars.getMConnectedVars.getMConnectedVars.Paths.getParents(List<Node> pi, int p, Graph g, boolean verbose, boolean allowSelectionBias) Returns the parents of the node at index p, calculated using Pearl's method.static NodeGraphUtils.getTrekSource(Graph graph, List<Node> trek) This method returns the source node of a given trek in a graph.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, boolean verbose) The extra-edge removal step for GFCI.GraphSaveLoadUtils.grabLayout(List<Node> nodes) grabLayout.static booleanGraphUtils.isClique(Collection<Node> set, Graph graph) Checks if the given set of nodes forms a clique in the specified graph.static booleanChecks if the given trek in a graph is a confounding trek.booleanPaths.isMConnectedTo(Node x, Node y, Set<Node> z, boolean allowSelectionBias) Detemrmines whether x and y are d-connected given z.booleanPaths.isMConnectedTo(Node x, Node y, Set<Node> z, Map<Node, Set<Node>> ancestors, boolean allowSelectionBias) Detemrmines whether x and y are d-connected given z.booleanPaths.isMConnectedTo(Node x, Node y, Set<Node> z, Map<Node, Set<Node>> ancestors, boolean allowSelectionBias) Detemrmines whether x and y are d-connected given z.booleanPaths.isMConnectedTo(Node x, Node y, Set<Node> z, Map<Node, Set<Node>> ancestors, boolean allowSelectionBias) Detemrmines 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, boolean allowSelectionBias) Determines whether one n ode is d-separated from another.booleanPaths.isMSeparatedFrom(Node node1, Node node2, Set<Node> z, Map<Node, Set<Node>> ancestors, boolean allowSelectionBias) Checks if two nodes are M-separated.booleanPaths.isMSeparatedFrom(Node node1, Node node2, Set<Node> z, Map<Node, Set<Node>> ancestors, boolean allowSelectionBias) Checks if two nodes are M-separated.booleanPaths.isMSeparatedFrom(Node node1, Node node2, Set<Node> z, Map<Node, Set<Node>> ancestors, boolean allowSelectionBias) Checks if two nodes are M-separated.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) loadGraphBNTPcMatrix.voidPaths.makeValidOrder(List<Node> order) Reorders the given order into a valid causal order for either a DAG or a CPDAG.GraphUtils.maximalCliques(Graph graph, List<Node> nodes) Finds all maximal cliques in a given graph.static GraphGraphSaveLoadUtils.parseGraphXml(nu.xom.Element graphElement, Map<String, Node> nodes) parseGraphXml.static StringGraphUtils.pathString(Graph graph, List<Node> path) pathString.static DagRandomGraph.randomDag(List<Node> nodes, int numLatentConfounders, int maxNumEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected) Generates a random Directed Acyclic Graph (DAG).static GraphRandomGraph.randomGraph(List<Node> nodes, int numLatentConfounders, int maxNumEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected) Generates a random graph based on the given parameters.static GraphRandomGraph.randomGraphRandomForwardEdges(List<Node> nodes, int numLatentConfounders, int numEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected) Generates a random graph with forward edges.static GraphRandomGraph.randomGraphRandomForwardEdges(List<Node> nodes, int numLatentConfounders, int numEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected, boolean layoutAsCircle) Generates a random graph with forward edges.static GraphRandomGraph.randomGraphUniform(List<Node> nodes, int numLatentConfounders, int maxNumEdges, int maxDegree, int maxIndegree, int maxOutdegree, boolean connected, int numIterations) Generates a random graph using UniformGraphGenerator with the specified parameters.booleanDag.removeNodes(List<Node> nodes) Removes the specified nodes from the graph.booleanEdgeListGraph.removeNodes(List<Node> newNodes) Iterates through the list and removes any permissible nodes found.booleanGraph.removeNodes(List<Node> nodes) Iterates through the list and removes any permissible nodes found.booleanLagGraph.removeNodes(List<Node> nodes) Iterates through the list and removes any permissible nodes found.booleanSemGraph.removeNodes(List<Node> nodes) Iterates through the list and removes any permissible nodes found.booleanTimeLagGraph.removeNodes(List<Node> nodes) Removes the specified nodes from the graph.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).voidSet the nodes of the graph.voidsetNodes.voidsetNodes.voidsetNodes.voidsetNodes.voidSets the nodes of the graph.Returns a subgraph of the current graph consisting only of the specified nodes.Constructs and returns a subgraph consisting of a given subset of the nodes of this graph together with the edges between them.Constructs and returns a subgraph consisting of a given subset of the nodes of this graph together with the edges between them.Constructs and returns a subgraph consisting of a given subset of the nodes of this graph together with the edges between them.Constructs and returns a subgraph consisting of a given subset of the nodes of this graph together with the edges between them.Returns a subgraph of the current graph based on the provided nodes.static GraphTrims the given graph based on the specified trimming style.Constructors 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) Constructor for IndependenceFact.IndependenceFact(Node x, Node y, Set<Node> z) Constructor for IndependenceFact.Constructor for NodePair.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.regress.Regresses the given target on the given regressors, yielding a regression plane, in which coefficients are given for each regressor plus the constant (if means have been specified, that is, for the last), and se, t, and p values are given for each regressor.regress.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 NodeModifierConstructorDescriptionRegressionDataset(Matrix data, List<Node> variables) Constructor for RegressionDataset. -
Uses of Node in edu.cmu.tetrad.search
Methods in edu.cmu.tetrad.search that return NodeModifier and TypeMethodDescriptionCstar.Record.getCauseNode()Returns the cause node associated with this record.Cstar.Record.getEffectNode()Retrieves the effect node of the record.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) Retrieves a variable with the given name.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.'Returns a map from nodes in V \ {Y} to their minimum effects.Finds the Markov blanket (MB) for a given target node.Given the target, this returns all the nodes in the Markov Blanket.Given the target, this returns all the nodes in the Markov Blanket.MarkovCheck.getAndersonDarlingTestAcceptsRejectsNodesForAllNodes(IndependenceTest independenceTest, Graph graph, Double threshold) Calculates the Anderson-Darling test and classifies nodes as accepted or rejected based on the given threshold.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().MarkovCheck.getConditioningNodes()Returns the nodes that are possible Z1,...,Zn for X _||_ Y | Z1,...,Zn.MarkovCheck.getIndependenceNodes()Returns the nodes that are possible X and Y for X _||_ Y | Z1,...,Zn.Fas.getNodes()Retrieves the list of nodes in the graph.Fasd.getNodes()Retrieves the list of nodes from the current object.Ida.NodeEffects.getNodes()Returns the nodes.IdaCheck.getNodes()Returns a list of nodes.IFas.getNodes()Returns the nodes searched over.Pcd.getNodes()Retrieves the list of nodes in the graph.SvarFas.getNodes()Retrieves the list of nodes from the current object.PermutationSearch.getOrder()Retrieves the order list.IdaCheck.getOrderedPairs()Retrieves a list of OrderedPair objects representing all possible pairs of distinct nodes in the graph.Boss.getParents()Returns the map from nodes to the sets of their parents.Boss.getParents()Returns the map from nodes to the sets of their parents.Sp.getParents()Retrieves a mapping of nodes to their parent nodes.Sp.getParents()Retrieves a mapping of nodes to their parent nodes.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()Returns the variables.CompositeIndependenceTest.getVariables()getVariables.Grasp.getVariables()Returns the variables.IndependenceTest.getVariables()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(List<Node> graphNodes, List<Node> independenceNodes, List<Node> conditioningNodes) Returns the variables of the independence test.PermutationSearch.getVariables()Retrieves the list of variables.Sp.getVariables()Returns the list of variables associated with this object.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) Adds similar edges between two nodes.Returns a map from nodes in V \ {Y} to their minimum effects.CompositeIndependenceTest.checkIndependence(Node x, Node y, Set<Node> z) checkIndependence.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) checkIndependence.IndTestIod.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence between two nodes given a set of nodes.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) Determines whether the variables in z determine x.Finds the Markov blanket (MB) for a given target node.Given the target, this returns all the nodes in the Markov Blanket.Given the target, this returns all the nodes in the Markov Blanket.Ida.getAbsTotalEffects(Node x, Node y) This method calculates the absolute total effects of node x on node y.Fas.getAmbiguousTriples(Node node) Retrieves the list of ambiguous triples involving the given node.Fasd.getAmbiguousTriples(Node node) Retrieves a list of ambiguous triples for the given node.IFas.getAmbiguousTriples(Node node) Returns the list of ambiguous triples found for a given node.SvarFas.getAmbiguousTriples(Node node) Retrieves the list of ambiguous triples involving the given node.Retrieves the GrowShrinkTree (GST) associated with the given Node.doubleIdaCheck.getIdaMinEffect(Node x, Node y) Gets the signed minimum absolute total effect value between two nodes.MarkovCheck.getLocalIndependenceFacts(Node x) Retrieves the list of local independence facts for a given node.doubleIdaCheck.getMaxTotalEffect(Node x, Node y) Returns the maximum total effect value between two nodes.doubleIdaCheck.getMinTotalEffect(Node x, Node y) Gets the minimum total effect value between two nodes.Return the node associated with the given variable in the graph.voidMarkovCheck.getPrecisionAndRecallOnMarkovBlanketGraph(Node x, Graph estimatedGraph, Graph trueGraph) Calculates the precision and recall on the Markov Blanket graph for a given node.Ida.getTotalEffects(Node x, Node y) Calculates the total effects of node x on node y.IndTestIod.getVariable(Node node) Returns the variable associated with the given node in the graph.voidSvarFges.removeSimilarEdges(Node x, Node y) Removes similar edges between two nodes.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.'CompositeIndependenceTest.checkIndependence(Node x, Node y, Set<Node> z) checkIndependence.IndependenceTest.checkIndependence(Node x, Node y, Set<Node> z) checkIndependence.IndTestIod.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence between two nodes given a set of nodes.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) Determines whether the variables in z determine x.doubleIdaCheck.getAverageSquaredDistance(List<OrderedPair<Node>> pairs) Returns the average of the squared distances between the true total effects and the IDA effect ranges the list of node pairs indicated.doubleIdaCheck.getAvgMaxSquaredDiffEstTrue(List<OrderedPair<Node>> pairs) Returns the average of the squared differences between the maximum total effects and the true total effects for the list of node pairs indicated.doubleIdaCheck.getAvgMinSquaredDiffEstTrue(List<OrderedPair<Node>> pairs) Returns the average of the squared differences between the minimum total effects and the true total effects for the list of node pairs indicated.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) Constructs 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) Constructs 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) Constructs 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.doubleIdaCheck.getSquaredDistance(OrderedPair<Node> pair) Calculates the squared distance of the true total effect to the [min, max] IDA effect range of the given (x, y) node pair, for x predicting y.doubleIdaCheck.getSquaredMaxTrueDist(OrderedPair<Node> pair) Returns the squared difference between the maximum total effect and the true total effect for the given pair of nodes.doubleIdaCheck.getSquaredMinTrueDistance(OrderedPair<Node> pair) Returns the squared difference between the minimum total effect and the true total effect for the given pair of nodes.doubleIdaCheck.getTrueTotalEffect(OrderedPair<Node> pair) Calculates the true total effect between two nodes in the graph.MarkovCheck.getVariables(List<Node> graphNodes, List<Node> independenceNodes, List<Node> conditioningNodes) Returns the variables of the independence test.default IndependenceTestIndependenceTest.indTestSubset(List<Node> vars) Returns an Independence test for a sublist of the variables.IndTestIod.indTestSubset(List<Node> vars) Calculates the independence test for a subset of variables.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.Searches for a graph using the given IFas instance and list 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.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) Searches a suborder of the variables.voidBoss.searchSuborder(List<Node> prefix, List<Node> suborder, Map<Node, GrowShrinkTree> gsts) Searches a suborder of the variables.voidSp.searchSuborder(List<Node> prefix, List<Node> suborder, Map<Node, GrowShrinkTree> gsts) Searches for the best suborder of nodes given a prefix and a suborder.voidSp.searchSuborder(List<Node> prefix, List<Node> suborder, Map<Node, GrowShrinkTree> gsts) Searches for the best suborder of nodes given a prefix and a suborder.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.voidSets the nodes.voidSets the order list for the search.voidPcMb.setVariables(List<Node> variables) Setter for the fieldvariables.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 present in the DataSet associated with this method.BdeuScore.getVariables()Retrieves the list of variables used in the object.ConditionalGaussianScore.getVariables()The variables of the score.DegenerateGaussianScore.getVariables()The variables of the score.DiscreteBicScore.getVariables()The variables of the score.EbicScore.getVariables()The variables of the score.GicScores.getVariables()The variables of the score.GraphScore.getVariables()The variables of the score.ImagesScore.getVariables()The variables of the score.IndTestScore.getVariables()The variables of the score.MvpScore.getVariables()The variables of the score.PoissonPriorScore.getVariables()The variables of the score.Score.getVariables()The variables of the score.SemBicScore.getVariables()The variables of the score.ZsbScore.getVariables()The variables of the score.Methods in edu.cmu.tetrad.search.score with parameters of type NodeModifier and TypeMethodDescriptionbooleanBdeuScore.determines(List<Node> z, Node y) Determines whether a set of nodes z determines a specific node y.booleanEbicScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanGicScores.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanImagesScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanIndTestScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanMvpScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanPoissonPriorScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and 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) Returns true iff the score determines the edge between x and y.booleanZsbScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.Method parameters in edu.cmu.tetrad.search.score with type arguments of type NodeModifier and TypeMethodDescriptionbooleanBdeuScore.determines(List<Node> z, Node y) Determines whether a set of nodes z determines a specific node y.booleanEbicScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanGicScores.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanImagesScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanIndTestScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanMvpScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.booleanPoissonPriorScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and 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) Returns true iff the score determines the edge between x and y.booleanZsbScore.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.voidDiscreteBicScore.setVariables(List<Node> variables) Sets the variables to a new list of the same size.voidGicScores.setVariables(List<Node> variables) Sets the variables of the dataset.voidSemBicScore.setVariables(List<Node> variables) Sets the variables of the covariance matrix.Returns a SEM BIC score for the given subset of 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) Retrieves a variable node based on its name.IndTestProbabilistic.getVariable(String name) Retrieves the Node object that matches the given name from the list of nodes.IndTestTrekSep.getVariable(String name) Gets the variable with the given name.Kci.getVariable(String name) Returns the variable of the given name.MsepTest.getVariable(String name) Returns theNodeobject with the given name.ScoreIndTest.getVariable(String name) Retrieves the Node object with the specified 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()Returns the list of variables used in this method.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 determining 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()Retrieves the list of variables associated with this object.IndTestMvpLrt.getVariables()Returns the list of searchVariables over which this independence checker is capable of determinining independence relations.IndTestProbabilistic.getVariables()Returns the list of variables used in this object.IndTestRegression.getVariables()Returns the list of variables associated with this object.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) Checks for independence between two nodes given a set of conditioning nodes.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) Determines whether two nodes are independent given a set of conditioning nodes.IndTestProbabilistic.checkIndependence(Node x, Node y, Node... z) Checks the independence fact in question and returns and independence result.IndTestProbabilistic.checkIndependence(Node x, Node y, Set<Node> _z) checkIndependence.IndTestRegression.checkIndependence(Node xVar, Node yVar, Set<Node> zList) Checks the independence between two variables, given a set of conditioning variables.IndTestTrekSep.checkIndependence(Node x, Node y, Set<Node> z) Determines independence between variables x and y, given the set of variables z.Kci.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence between two nodes given a set of conditioning variables.MsepTest.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence between two nodes with respect to a set of conditioning nodes.ScoreIndTest.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence between two nodes given a set of additional nodes.booleanIndTestChiSquare.determines(List<Node> z, Node x) Determines whether variable x is independent of variable y given a list of conditioning nodes.booleanIndTestConditionalCorrelation.determines(List<Node> z, Node x) Determines whether the nodes z determine x.booleanIndTestConditionalGaussianLrt.determines(List<Node> z, Node y) Determines whether a given list of nodes (z) determines a node (y).booleanIndTestDegenerateGaussianLrt.determines(List<Node> z, Node y) Determines whether a given list of nodes z determines a node y.booleanIndTestFisherZ.determines(List<Node> z, Node x) Determines if a given Node x is determined by a list of Nodes z.booleanIndTestFisherZConcatenateResiduals.determines(List<Node> z, Node x) Determines whether the z nodes determine the x node.booleanIndTestFisherZFisherPValue.determines(List<Node> z, Node x) Determines if a given list of conditioning nodes (z) determines the value of a specific node (x).booleanIndTestGSquare.determines(Set<Node> _z, Node x) Determines whether variable x is independent of a set of variables _z.booleanIndTestHsic.determines(List<Node> z, Node x) Determines whether variable x is independent of variable y given a list of conditioning variables z.booleanIndTestIndependenceFacts.determines(List<Node> z, Node y) Determines if the given list of nodes (z) determines the specified node (y).booleanIndTestMulti.determines(List<Node> z, Node x) Determines whether variable x is independent of variable y given a list of conditioning variables z.booleanIndTestMvpLrt.determines(List<Node> z, Node y) Determines whether two nodes are independent given a set of conditioning nodes.booleanIndTestProbabilistic.determines(Set<Node> z, Node y) Determines whether a given set of nodes, z, determines another node, y.booleanIndTestRegression.determines(List<Node> zList, Node xVar) Determines if a variable xVar can be determined by a list of conditioning variables zList.booleanIndTestTrekSep.determines(List<Node> z, Node x) Determines the independence between a set of variables z and a variable x.booleanKci.determines(List<Node> z, Node y) Determines the independence between a set of nodes and a target node.booleanMsepTest.determines(List<Node> z, Node x1) Determines if a node is m-separated from a set of conditioning nodes.booleanScoreIndTest.determines(List<Node> z, Node y) Determines the result of an independence test between a set of variables and a target variable.Returns the pvalue if the fact of X _||_ Y | Z is within the cache of results for independence fact.doubleReturns the p-value for x _||_ y | 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) Returns the probability of the constraint x op y | z.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) Checks for independence between two nodes given a set of conditioning nodes.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) Determines whether two nodes are independent given a set of conditioning nodes.IndTestProbabilistic.checkIndependence(Node x, Node y, Set<Node> _z) checkIndependence.IndTestRegression.checkIndependence(Node xVar, Node yVar, Set<Node> zList) Checks the independence between two variables, given a set of conditioning variables.IndTestTrekSep.checkIndependence(Node x, Node y, Set<Node> z) Determines independence between variables x and y, given the set of variables z.Kci.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence between two nodes given a set of conditioning variables.MsepTest.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence between two nodes with respect to a set of conditioning nodes.ScoreIndTest.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence between two nodes given a set of additional nodes.booleanIndTestChiSquare.determines(List<Node> z, Node x) Determines whether variable x is independent of variable y given a list of conditioning nodes.booleanIndTestConditionalCorrelation.determines(List<Node> z, Node x) Determines whether the nodes z determine x.booleanIndTestConditionalGaussianLrt.determines(List<Node> z, Node y) Determines whether a given list of nodes (z) determines a node (y).booleanIndTestDegenerateGaussianLrt.determines(List<Node> z, Node y) Determines whether a given list of nodes z determines a node y.booleanIndTestFisherZ.determines(List<Node> z, Node x) Determines if a given Node x is determined by a list of Nodes z.booleanIndTestFisherZConcatenateResiduals.determines(List<Node> z, Node x) Determines whether the z nodes determine the x node.booleanIndTestFisherZFisherPValue.determines(List<Node> z, Node x) Determines if a given list of conditioning nodes (z) determines the value of a specific node (x).booleanIndTestGSquare.determines(Set<Node> _z, Node x) Determines whether variable x is independent of a set of variables _z.booleanIndTestHsic.determines(List<Node> z, Node x) Determines whether variable x is independent of variable y given a list of conditioning variables z.booleanIndTestIndependenceFacts.determines(List<Node> z, Node y) Determines if the given list of nodes (z) determines the specified node (y).booleanIndTestMulti.determines(List<Node> z, Node x) Determines whether variable x is independent of variable y given a list of conditioning variables z.booleanIndTestMvpLrt.determines(List<Node> z, Node y) Determines whether two nodes are independent given a set of conditioning nodes.booleanIndTestProbabilistic.determines(Set<Node> z, Node y) Determines whether a given set of nodes, z, determines another node, y.booleanIndTestRegression.determines(List<Node> zList, Node xVar) Determines if a variable xVar can be determined by a list of conditioning variables zList.booleanIndTestTrekSep.determines(List<Node> z, Node x) Determines the independence between a set of variables z and a variable x.booleanKci.determines(List<Node> z, Node y) Determines the independence between a set of nodes and a target node.booleanMsepTest.determines(List<Node> z, Node x1) Determines if a node is m-separated from a set of conditioning nodes.booleanScoreIndTest.determines(List<Node> z, Node y) Determines the result of an independence test between a set of variables and a target variable.Returns the pvalue if the fact of X _||_ Y | Z is within the cache of results for independence fact.doubleReturns the p-value for x _||_ y | z.IndTestChiSquare.indTestSubset(List<Node> nodes) Checks conditional independence between variables in a subset.IndTestConditionalCorrelation.indTestSubset(List<Node> vars) Constructs a new Independence test which checks independence facts based on the correlation data implied by the given data set (must be continuous).IndTestConditionalGaussianLrt.indTestSubset(List<Node> vars) This method returns an instance of the IndependenceTest interface that can test the independence of a subset of variables.IndTestDegenerateGaussianLrt.indTestSubset(List<Node> vars) Subsets the variables used in the independence test.IndTestFisherZ.indTestSubset(List<Node> vars) Creates a new independence test instance for a subset of the variables.IndTestFisherZConcatenateResiduals.indTestSubset(List<Node> vars) Returns an Independence test for a sublist of the variables.IndTestFisherZFisherPValue.indTestSubset(List<Node> vars) Returns an Independence test for a sublist of the variables.IndTestGSquare.indTestSubset(List<Node> vars) Performs an independence test on a subset of variables.IndTestHsic.indTestSubset(List<Node> vars) Subset of variables for independence testing.IndTestIndependenceFacts.indTestSubset(List<Node> vars) Returns anIndependenceTestobject for a sublist of variables.IndTestMulti.indTestSubset(List<Node> vars) Returns an Independence test for a sublist of the variables.IndTestMvpLrt.indTestSubset(List<Node> vars) Returns an Independence test for a sublist of the variables.IndTestProbabilistic.indTestSubset(List<Node> vars) Returns an Independence test for a sublist of the variables.IndTestRegression.indTestSubset(List<Node> vars) Performs an independence test for a sublist of variables.IndTestTrekSep.indTestSubset(List<Node> vars) Determines independence between variables in a given subset.Kci.indTestSubset(List<Node> vars) MsepTest.indTestSubset(List<Node> vars) Conducts an independence test on a subset of variables.ScoreIndTest.indTestSubset(List<Node> vars) Tests the independence between variables in a given sublist.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) Returns the probability of the constraint x op y | z.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.Bes.Arrow.getA()Returns the first node.Bes.Arrow.getB()Returns the second node.Tetrad.getI()Getter for the fieldi.Tetrad.getJ()Getter for the fieldj.Tetrad.getK()Getter for the fieldk.Tetrad.getL()Getter for the fieldl.GrowShrinkTree.getNode()Getter for the fieldnode.static Nodetranslate.Methods in edu.cmu.tetrad.search.utils that return types with arguments of type NodeModifier and TypeMethodDescriptionLogUtilsSearch.buildIndexing(List<Node> nodes) buildIndexing.ClusterUtils.clustersToPartition(Clusters clusters, List<Node> variables) Converts a list of indices into a list of Nodes representing a cluster.MimUtils.convertToClusters2(Graph clusterGraph) convertToClusters2.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) getAncestors.TeyssierScorer.getChildren(int p) Returns the children of a node v.TeyssierScorer.getChildren(Node v) Returns the children of a node v.PossibleMConnectingPath.getConditions()Getter for the fieldconditions.TeyssierScorer.getEdges()Returns a list of edges for the current graph as a list of ordered pairs.GrowShrinkTree.getFirstLayer()getFirstLayer.GrowShrinkTree.getForbidden()Getter for the fieldforbidden.Tetrad.getNodes()getNodes.TeyssierScorer.getOrderShallow()Returns the current permutation without making a copy.Bes.Arrow.getParents()Returns the set of nodes that are in TNeighbors.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()Getter for the fieldpath.TeyssierScorer.getPi()Getter for the fieldpi.TeyssierScorer.getPrefix(int i) getPrefix.GraphSearchUtils.getReachableNodes(List<Node> initialNodes, LegalPairs legalPairs, List<Node> c, List<Node> d, Graph graph, int maxPathLength) getReachableNodes.GrowShrinkTree.getRequired()Getter for the fieldrequired.getSepset.PossibleMsepFci.getSepset(IndependenceTest test, Node node1, Node node2) Getter for the fieldsepset.getSepset.Retrieves the sepset (separating set) between two nodes, or null if no such sepset is found.Returns the set of nodes in the sepset between two given nodes, or null if no sepset is found.Returns the set of nodes that form the sepset (separating set) between two given nodes.Retrieves the separation set (sepset) between two nodes.Retrieves the sepset between two nodes.DagSepsets.getSepsetContaining(Node a, Node b, Set<Node> s) Returns the sepset containing nodes 'a' and 'b' that also contains all the nodes in the given set 's'.SepsetProducer.getSepsetContaining(Node a, Node b, Set<Node> s) Returns the subset for a and b, where this sepset is expected to contain all the nodes in s.SepsetsGreedy.getSepsetContaining(Node i, Node k, Set<Node> s) Retrieves a sepset (separating set) between two nodes containing a set of nodes, or null if no such sepset is found.SepsetsMaxP.getSepsetContaining(Node i, Node k, Set<Node> s) Returns the set of nodes in the sepset between two given nodes containing a given set of separator nodes, or null if no sepset is found.SepsetsMinP.getSepsetContaining(Node i, Node k, Set<Node> s) Returns the set of nodes that form the sepset (separating set) between two given nodes containing all the nodes in the given set.SepsetsPossibleMsep.getSepsetContaining(Node i, Node k, Set<Node> s) Retrieves the separation set (sepset) between two nodes i and k that contains a given set of nodes s.SepsetsSet.getSepsetContaining(Node a, Node b, Set<Node> s) Retrieves the sepset for a and b, where we are expecting this sepset to contain all the nodes in s.SepsetsMaxP.getSepsetsLists(Node x, Node y, Node z, IndependenceTest test, int depth, boolean verbose) getSepsetsLists.SepsetsMinP.getSepsetsLists(Node x, Node y, Node z, IndependenceTest test, int depth, boolean verbose) getSepsetsLists.TeyssierScorer.getShuffledVariables()getShuffledVariables.TeyssierScorer.getSkeleton()getSkeleton.Bes.Arrow.getTNeighbors()Returns the set of nodes that are in TNeighbors.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()getVariables.DeltaSextadTest.getVariables()Returns the variables of the data being used.GrowShrinkTree.getVariables()getVariables.SepsetProducer.getVariables()getVariables.SepsetsGreedy.getVariables()getVariables.SepsetsMaxP.getVariables()getVariables.SepsetsMinP.getVariables()getVariables.SepsetsPossibleMsep.getVariables()getVariables.SepsetsSet.getVariables()getVariables.TetradTest.getVariables()getVariables.TetradTestContinuous.getVariables()Getter for the fieldvariables.TetradTestDiscrete.getVariables()getVariables.TetradTestPopulation.getVariables()getVariables.GraphoidAxioms.GraphoidIndFact.getX()Returns the set of nodes X.GraphoidAxioms.GraphoidIndFact.getY()Returns the set of nodes Y.GraphoidAxioms.GraphoidIndFact.getZ()Returns the set of nodes Z.MeekRules.orientImplied(Graph graph) Uses the Meek rules to do as many orientations in the given graph as possible.powerSet.purify.purify.purify.ClusterSignificance.variablesForIndices(List<Integer> cluster, List<Node> variables) Converts a list of indices into a list of Nodes representing a cluster.Converts a list of indices into a list of Nodes representing a cluster.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) basicCpdagRestricted2.booleanReturns true iff [a, b, c] is a collider.static StringLogUtilsSearch.colliderOrientedMsg(Node x, Node y, Node z) colliderOrientedMsg.static StringcolliderOrientedMsg.static StringLogUtilsSearch.colliderOrientedMsg(String note, Node x, Node y, Node z) colliderOrientedMsg.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.static StringLogUtilsSearch.dependenceFactMsg(Node x, Node y, Set<Node> condSet, double pValue) dependenceFactMsg.static StringLogUtilsSearch.determinismDetected(Set<Node> sepset, Node x) determinismDetected.static booleanDagToPag.existsInducingPathInto(Node x, Node y, Graph graph) existsInducingPathInto.static booleanTsDagToPag.existsInducingPathInto(Node x, Node y, Graph graph, Knowledge knowledge) existsInducingPathInto.static booleanTsDagToPag.existsInducingPathVisitts(Graph graph, Node a, Node b, Node x, Node y, LinkedList<Node> path, Knowledge knowledge) existsInducingPathVisitts.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) getAncestors.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) getCpcTripleType.Getter for the fieldindex.TeyssierScorer.getParents(Node v) Returns the parents of a node v.doubledoubleLooks up the p-value for {x, y}doubleCalculates the p-value for a statistical test a _||_ b | sepset.doubleReturns the p-value for the independence test between two nodes, given a set of separator nodes.doubleReturns the p-value for the independence test between two nodes, given a set of separator nodes.doubleReturns the p-value for the independence test between two nodes, given a set of separator nodes.doubleReturns the p-value for the independence test between two nodes, given a set of separator nodes.doublestatic StringLogUtilsSearch.getScoreFact(Node i, List<Node> parents) getScoreFact.getSepset.PossibleMsepFci.getSepset(IndependenceTest test, Node node1, Node node2) Getter for the fieldsepset.getSepset.Retrieves the sepset (separating set) between two nodes, or null if no such sepset is found.Returns the set of nodes in the sepset between two given nodes, or null if no sepset is found.Returns the set of nodes that form the sepset (separating set) between two given nodes.Retrieves the separation set (sepset) between two nodes.Retrieves the sepset between two nodes.DagSepsets.getSepsetContaining(Node a, Node b, Set<Node> s) Returns the sepset containing nodes 'a' and 'b' that also contains all the nodes in the given set 's'.SepsetProducer.getSepsetContaining(Node a, Node b, Set<Node> s) Returns the subset for a and b, where this sepset is expected to contain all the nodes in s.SepsetsGreedy.getSepsetContaining(Node i, Node k, Set<Node> s) Retrieves a sepset (separating set) between two nodes containing a set of nodes, or null if no such sepset is found.SepsetsMaxP.getSepsetContaining(Node i, Node k, Set<Node> s) Returns the set of nodes in the sepset between two given nodes containing a given set of separator nodes, or null if no sepset is found.SepsetsMinP.getSepsetContaining(Node i, Node k, Set<Node> s) Returns the set of nodes that form the sepset (separating set) between two given nodes containing all the nodes in the given set.SepsetsPossibleMsep.getSepsetContaining(Node i, Node k, Set<Node> s) Retrieves the separation set (sepset) between two nodes i and k that contains a given set of nodes s.SepsetsSet.getSepsetContaining(Node a, Node b, Set<Node> s) Retrieves the sepset for a and b, where we are expecting this sepset to contain all the nodes in s.SepsetsMaxP.getSepsetsLists(Node x, Node y, Node z, IndependenceTest test, int depth, boolean verbose) getSepsetsLists.SepsetsMinP.getSepsetsLists(Node x, Node y, Node z, IndependenceTest test, int depth, boolean verbose) getSepsetsLists.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) independenceFact.static StringLogUtilsSearch.independenceFactMsg(Node x, Node y, Set<Node> condSet, double pValue) independenceFactMsg.intReturn the index of v in the current permutation.static booleanFciOrient.isArrowheadAllowed(Node x, Node y, Graph graph, Knowledge knowledge) isArrowheadAllowed.booleanGrowShrinkTree.isForbidden(Node node) isForbidden.booleanDagSepsets.isIndependent(Node a, Node b, Set<Node> sepset) isIndependent.booleanSepsetProducer.isIndependent(Node d, Node c, Set<Node> sepset) isIndependent.booleanSepsetsGreedy.isIndependent(Node a, Node b, Set<Node> sepset) isIndependent.booleanSepsetsMaxP.isIndependent(Node a, Node b, Set<Node> sepset) Determines if two nodes are independent given a set of separator nodes.booleanSepsetsMinP.isIndependent(Node a, Node b, Set<Node> sepset) Determines if two nodes are independent given a set of separator nodes.booleanSepsetsPossibleMsep.isIndependent(Node d, Node c, Set<Node> sepset) isIndependent.booleanSepsetsSet.isIndependent(Node a, Node b, Set<Node> sepset) isIndependent.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) isLegalFirstEdge.booleanisLegalPair.booleanGrowShrinkTree.isRequired(Node node) isRequired.booleanDagSepsets.isUnshieldedCollider(Node i, Node j, Node k) isUnshieldedCollider.booleanSepsetProducer.isUnshieldedCollider(Node i, Node j, Node k) isUnshieldedCollider.booleanSepsetsGreedy.isUnshieldedCollider(Node i, Node j, Node k) isUnshieldedCollider.booleanSepsetsMaxP.isUnshieldedCollider(Node i, Node j, Node k) isUnshieldedCollider.booleanSepsetsMinP.isUnshieldedCollider(Node i, Node j, Node k) isUnshieldedCollider.booleanSepsetsPossibleMsep.isUnshieldedCollider(Node i, Node j, Node k) isUnshieldedCollider.booleanSepsetsSet.isUnshieldedCollider(Node i, Node j, Node k) isUnshieldedCollider.voidMoves v to a new index.static voidPcCommon.orientCollider(Node x, Node y, Node z, PcCommon.ConflictRule conflictRule, Graph graph, boolean verbose) Orient a single unshielded triple, x*-*y*-*z, in a graph.booleanparent.voidruleR1.voidTries to apply Zhang's rule R10 to a pair of nodes A and C which are assumed to be such that Ao->C.voidruleR2.booleanTries 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) Sets bandwidth from data using default methodvoidKernelGaussian.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.booleanMoves j to before k and moves all the ancestors of j betwween k and j to before k.Method 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.LogUtilsSearch.buildIndexing(List<Node> nodes) buildIndexing.booleanTrue iff the nodes in W form a clique in the current DAG.ClusterUtils.clustersToPartition(Clusters clusters, List<Node> variables) Converts a list of indices into a list of Nodes representing a cluster.static StringcolliderOrientedMsg.static List<int[]>Converts a list of indices into a list of Nodes representing a cluster.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) dependenceFactMsg.static StringLogUtilsSearch.determinismDetected(Set<Node> sepset, Node x) determinismDetected.static booleanTsDagToPag.existsInducingPathVisitts(Graph graph, Node a, Node b, Node x, Node y, LinkedList<Node> path, Knowledge knowledge) existsInducingPathVisitts.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.doubledoubleCalculates the p-value for a statistical test a _||_ b | sepset.doubleReturns the p-value for the independence test between two nodes, given a set of separator nodes.doubleReturns the p-value for the independence test between two nodes, given a set of separator nodes.doubleReturns the p-value for the independence test between two nodes, given a set of separator nodes.doubleReturns the p-value for the independence test between two nodes, given a set of separator nodes.doubleGraphSearchUtils.getReachableNodes(List<Node> initialNodes, LegalPairs legalPairs, List<Node> c, List<Node> d, Graph graph, int maxPathLength) getReachableNodes.static StringLogUtilsSearch.getScoreFact(int i, int[] parents, List<Node> variables) getScoreFact.static StringLogUtilsSearch.getScoreFact(Node i, List<Node> parents) getScoreFact.DagSepsets.getSepsetContaining(Node a, Node b, Set<Node> s) Returns the sepset containing nodes 'a' and 'b' that also contains all the nodes in the given set 's'.SepsetProducer.getSepsetContaining(Node a, Node b, Set<Node> s) Returns the subset for a and b, where this sepset is expected to contain all the nodes in s.SepsetsGreedy.getSepsetContaining(Node i, Node k, Set<Node> s) Retrieves a sepset (separating set) between two nodes containing a set of nodes, or null if no such sepset is found.SepsetsMaxP.getSepsetContaining(Node i, Node k, Set<Node> s) Returns the set of nodes in the sepset between two given nodes containing a given set of separator nodes, or null if no sepset is found.SepsetsMinP.getSepsetContaining(Node i, Node k, Set<Node> s) Returns the set of nodes that form the sepset (separating set) between two given nodes containing all the nodes in the given set.SepsetsPossibleMsep.getSepsetContaining(Node i, Node k, Set<Node> s) Retrieves the separation set (sepset) between two nodes i and k that contains a given set of nodes s.SepsetsSet.getSepsetContaining(Node a, Node b, Set<Node> s) Retrieves the sepset for a and b, where we are expecting this sepset to contain all the nodes in s.static StringLogUtilsSearch.independenceFact(Node x, Node y, Set<Node> condSet) independenceFact.static StringLogUtilsSearch.independenceFactMsg(Node x, Node y, Set<Node> condSet, double pValue) independenceFactMsg.booleanDagSepsets.isIndependent(Node a, Node b, Set<Node> sepset) isIndependent.booleanSepsetProducer.isIndependent(Node d, Node c, Set<Node> sepset) isIndependent.booleanSepsetsGreedy.isIndependent(Node a, Node b, Set<Node> sepset) isIndependent.booleanSepsetsMaxP.isIndependent(Node a, Node b, Set<Node> sepset) Determines if two nodes are independent given a set of separator nodes.booleanSepsetsMinP.isIndependent(Node a, Node b, Set<Node> sepset) Determines if two nodes are independent given a set of separator nodes.booleanSepsetsPossibleMsep.isIndependent(Node d, Node c, Set<Node> sepset) isIndependent.booleanSepsetsSet.isIndependent(Node a, Node b, Set<Node> sepset) isIndependent.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 methodbooleanisLegalPair.static voidLogs the clusters.voidFciOrient.orientTailPath(List<Node> path, Graph graph) Orients every edge on a path as undirected (i.e.static ClustersClusterUtils.partitionToClusters(List<List<Node>> partition) Converts a list of indices into a list of Nodes representing a cluster.static voidGraphSearchUtils.pcOrientbk(Knowledge bk, Graph graph, List<Node> nodes, boolean verbose) Orients according to background knowledge.powerSet.purify.purify.purify.doubleScores the given permutation.Runs the search over the given list of nodes only, returning the search 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) setKnowledge.voidBes.Arrow.setTNeighbors(Set<Node> TNeighbors) Sets the set of nodes that are in TNeighbors.doubletrace.doubletrace.static Nodetranslate.Converts a list of indices into a list of Nodes representing a cluster.Constructors in edu.cmu.tetrad.search.utils with parameters of type NodeModifierConstructorDescriptionConstructor for GrowShrinkTree.KernelGaussian(DataSet dataset, Node node) Creates a new Gaussian kernel using the median distance between points to set the bandwidthConstructor for Tetrad.Constructor for Tetrad.Constructor parameters in edu.cmu.tetrad.search.utils with type arguments of type NodeModifierConstructorDescriptionClusterSignificance(List<Node> variables, DataModel dataModel) Constructs a new cluster significance object.GraphoidAxioms(Set<GraphoidAxioms.GraphoidIndFact> facts, List<Node> nodes) Constructor.GraphoidAxioms(Set<GraphoidAxioms.GraphoidIndFact> facts, List<Node> nodes, Map<GraphoidAxioms.GraphoidIndFact, String> textSpecs) Constructor.Constructor.Constructor for GrowShrinkTree.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()Getter for the fieldi.Sextad.getJ()Getter for the fieldj.Sextad.getK()Getter for the fieldk.Sextad.getL()Getter for the fieldl.Sextad.getM()Getter for the fieldm.Sextad.getN()Getter for the fieldn.getNode.IndTestFisherZRecursive.getVariable(String name) Returns The variable by the given name.IndTestPositiveCorr.getVariable(String name) Retrieves the node associated with the given variable name.IndTestSepsetDci.getVariable(Node node) getVariable.IndTestSepsetDci.getVariable(String name) Retrieves the variable with the specified name.ProbabilisticMapIndependence.getVariable(String name) Returns The variable by the given name.Methods in edu.cmu.tetrad.search.work_in_progress that return types with arguments of type NodeModifier and TypeMethodDescriptionbestOrder.Given the target, this returns all the nodes in the Markov Blanket.Given the target, this returns all the nodes in the Markov Blanket.Given the target, this returns all the nodes in the Markov Blanket.Given the target, this returns all the nodes in the Markov Blanket.get.Retrieves the sepset previously set for {x, y}, or null if no such set was previously set.VcFas.getApparentlyNonadjacencies()Getter for the fieldapparentlyNonadjacencies.getInputs.DMSearch.LatentStructure.getLatentEffects(Node latent) getLatentEffects.DMSearch.LatentStructure.getLatents()getLatents.FasFdr.getNodes()Returns the nodes searched over.Sextad.getNodes()getNodes.VcFas.getNodes()getNodes.MagSemBicScore.getOrder()Returns the order.DMSearch.LatentStructure.getOutputs(Node latent) getOutputs.Getter for the fieldpc.SepsetMapDci.getSeparatedPairs()getSeparatedPairs.Retrieves the set of all condioning sets for {x, y} or null if no such set was ever setGraspTol.getVariables()Getter for the fieldvariables.IndTestCramerT.getVariables()Retrieves the list of variables used in the independence test.IndTestFisherZPercentIndependent.getVariables()Getter for the fieldvariables.IndTestFisherZRecursive.getVariables()Getter for the fieldvariables.IndTestMixedMultipleTTest.getVariables()Retrieves the list of variables used in the original data set.IndTestMnlrLr.getVariables()getVariables.IndTestMultinomialLogisticRegression.getVariables()getVariables.IndTestPositiveCorr.getVariables()Retrieves the list of variables used in the independence test.IndTestSepsetDci.getVariables()getVariables.MagSemBicScore.getVariables()The variables of the score.MnlrScore.getVariables()The variables of the score.ProbabilisticMapIndependence.getVariables()getVariables.SemBicScoreDeterministic.getVariables()The variables of the score.GraspTol.grasp(@NotNull TeyssierScorer scorer) grasp.treks.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) addRecord.IndTestCramerT.checkIndependence(Node x, Node y, Set<Node> _z) Checks the independence between two nodes given a set of conditioning nodes.IndTestFisherZPercentIndependent.checkIndependence(Node x, Node y, Set<Node> _z) Checks the independence between two nodes x and y given a set of conditioning nodes z.IndTestFisherZRecursive.checkIndependence(Node x, Node y, Set<Node> z) checkIndependence.IndTestMixedMultipleTTest.checkIndependence(Node x, Node y, Set<Node> z) Checks for independence between two nodes.IndTestMnlrLr.checkIndependence(Node x, Node y, Set<Node> _z) Checks the independence between two nodes given a set of conditioning nodes.IndTestMultinomialLogisticRegression.checkIndependence(Node x, Node y, Set<Node> z) Checks for independence between two nodes, given a set of conditioning nodes.IndTestPositiveCorr.checkIndependence(Node x0, Node y0, Set<Node> _z0) Checks the independence between two nodes, given a set of conditioning nodes.IndTestSepsetDci.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence between two nodes, given a set of conditioning nodes.ProbabilisticMapIndependence.checkIndependence(Node x, Node y, Node... z) Checks the independence fact in question and returns and independence result.ProbabilisticMapIndependence.checkIndependence(Node x, Node y, Set<Node> _z) checkIndependence.booleanDMSearch.LatentStructure.containsLatent(Node latent) containsLatent.booleanIndTestCramerT.determines(List<Node> z, Node x) Determines whether the given variables are conditionally independent.booleanIndTestFisherZPercentIndependent.determines(List z, Node x) Determines the independence between a list of conditioning variables (z) and a target variable (x).booleanIndTestFisherZRecursive.determines(Set<Node> _z, Node x) Returns true if y is determined the variable in z.booleanIndTestMixedMultipleTTest.determines(List<Node> z, Node y) Determines if a given set of nodes z determines the node y.booleanIndTestMnlrLr.determines(List<Node> z, Node y) Determines the independence relation between a list of conditioning nodes and a target node.booleanIndTestMultinomialLogisticRegression.determines(List<Node> z, Node y) Determines if Node y is determined by the given list of Nodes z.booleanIndTestPositiveCorr.determines(List<Node> z, Node x) Determines if there exists a causal relationship between the nodes in z and node x.booleanIndTestSepsetDci.determines(List<Node> z, Node x1) Determines if a given Node is present in a List of Nodes.booleanProbabilisticMapIndependence.determines(Set<Node> z, Node y) Returns true if y is determined the variable in z.booleanSemBicScoreDeterministic.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.Given the target, this returns all the nodes in the Markov Blanket.Given the target, this returns all the nodes in the Markov Blanket.Given the target, this returns all the nodes in the Markov Blanket.Given the target, this returns all the nodes in the Markov Blanket.static voidSampleVcpc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidSampleVcpcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidVcPc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidVcPcAlt.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidVcPcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.get.Retrieves the sepset previously set for {x, y}, or null if no such set was previously set.FasFdr.getAmbiguousTriples(Node node) Returns the list of ambiguous triples found for a given node.getInputs.DMSearch.LatentStructure.getLatentEffects(Node latent) getLatentEffects.getNode.DMSearch.LatentStructure.getOutputs(Node latent) getOutputs.Getter for the fieldpc.VcPc.getPopulationTripleType(Node x, Node y, Node z, IndependenceTest test, int depth, Graph graph, boolean verbose) getPopulationTripleType.VcPcFast.getPopulationTripleType(Node x, Node y, Node z, IndependenceTest test, int depth, Graph graph, boolean verbose) getPopulationTripleType.Retrieves the set of all condioning sets for {x, y} or null if no such set was ever setIndTestSepsetDci.getVariable(Node node) getVariable.static booleanSampleVcpcFast.isArrowheadAllowed1(Node from, Node to, Knowledge knowledge) isArrowheadAllowed1.static booleanVcPc.isArrowheadAllowed1(Node from, Node to, Knowledge knowledge) isArrowheadAllowed1.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) probConstraint.voidDMSearch.LatentStructure.removeLatent(Node latent) removeLatent.voidSets the sepset for {x, y} to be z.voidSepsetMapDci.set(Node x, LinkedHashSet<Node> z) set.treks.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) addRecord.ResolveSepsetsDci.allNodePairs(List<Node> nodes) Generates NodePairs of all possible pairs of nodes from given list of nodes.bestOrder.IndTestCramerT.checkIndependence(Node x, Node y, Set<Node> _z) Checks the independence between two nodes given a set of conditioning nodes.IndTestFisherZPercentIndependent.checkIndependence(Node x, Node y, Set<Node> _z) Checks the independence between two nodes x and y given a set of conditioning nodes z.IndTestFisherZRecursive.checkIndependence(Node x, Node y, Set<Node> z) checkIndependence.IndTestMixedMultipleTTest.checkIndependence(Node x, Node y, Set<Node> z) Checks for independence between two nodes.IndTestMnlrLr.checkIndependence(Node x, Node y, Set<Node> _z) Checks the independence between two nodes given a set of conditioning nodes.IndTestMultinomialLogisticRegression.checkIndependence(Node x, Node y, Set<Node> z) Checks for independence between two nodes, given a set of conditioning nodes.IndTestPositiveCorr.checkIndependence(Node x0, Node y0, Set<Node> _z0) Checks the independence between two nodes, given a set of conditioning nodes.IndTestSepsetDci.checkIndependence(Node x, Node y, Set<Node> z) Checks the independence between two nodes, given a set of conditioning nodes.ProbabilisticMapIndependence.checkIndependence(Node x, Node y, Set<Node> _z) checkIndependence.booleanIndTestCramerT.determines(List<Node> z, Node x) Determines whether the given variables are conditionally independent.booleanIndTestFisherZRecursive.determines(Set<Node> _z, Node x) Returns true if y is determined the variable in z.booleanIndTestMixedMultipleTTest.determines(List<Node> z, Node y) Determines if a given set of nodes z determines the node y.booleanIndTestMnlrLr.determines(List<Node> z, Node y) Determines the independence relation between a list of conditioning nodes and a target node.booleanIndTestMultinomialLogisticRegression.determines(List<Node> z, Node y) Determines if Node y is determined by the given list of Nodes z.booleanIndTestPositiveCorr.determines(List<Node> z, Node x) Determines if there exists a causal relationship between the nodes in z and node x.booleanIndTestSepsetDci.determines(List<Node> z, Node x1) Determines if a given Node is present in a List of Nodes.booleanProbabilisticMapIndependence.determines(Set<Node> z, Node y) Returns true if y is determined the variable in z.booleanSemBicScoreDeterministic.determines(List<Node> z, Node y) Returns true iff the score determines the edge between x and y.static voidSampleVcpc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidSampleVcpc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidSampleVcpcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidSampleVcpcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidVcPc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidVcPc.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidVcPcAlt.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidVcPcAlt.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidVcPcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.static voidVcPcFast.futureNodeVisit(Graph graph, Node b, LinkedList<Node> path, Set<Node> futureNodes) futureNodeVisit.IndTestCramerT.indTestSubset(List<Node> vars) This method performs an independence test based on a given sublist of variables.IndTestFisherZPercentIndependent.indTestSubset(List<Node> vars) Performs an independence test on a subset of variables.IndTestFisherZRecursive.indTestSubset(List<Node> vars) Returns an Independence test for a sublist of the variables.IndTestMixedMultipleTTest.indTestSubset(List<Node> vars) IndTestMnlrLr.indTestSubset(List<Node> vars) This method returns an independence test for a sublist of variables.IndTestMultinomialLogisticRegression.indTestSubset(List<Node> vars) Performs an independence test for a sublist of variables.IndTestPositiveCorr.indTestSubset(List<Node> vars) Performs an independence test on a subset of variables.IndTestSepsetDci.indTestSubset(List<Node> vars) Determines independence between a subset of variables.ProbabilisticMapIndependence.indTestSubset(List<Node> vars) Returns an Independence test for a sublist of the variables.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 trekRuns 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) set.voidSets the order.voidIndTestFisherZRecursive.setVariables(List<Node> variables) Setter for the fieldvariables.voidIndTestPositiveCorr.setVariables(List<Node> variables) Sets the variables used in the independence test.voidSemBicScoreDeterministic.setVariables(List<Node> variables) Setter for the fieldvariables.Constructors in edu.cmu.tetrad.search.work_in_progress with parameters of type NodeModifierConstructorDescriptionConstructor for Sextad.Constructor for Sextad.Constructor 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.Constructor for GraspTol.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) Retrieves the error node associated with the given node.Node[]ConnectionFunction.getInputNodes()getInputNodes.Returns the Node with the given name.SemEvidence.getNode(int nodeIndex) getNode.SemManipulation.getNode(int nodeIndex) getNode.Parameter.getNodeA()Getter for the fieldnodeA.Parameter.getNodeB()Getter for the fieldnodeB.SemIm.getVariableNode(String name) getVariableNode.Methods in edu.cmu.tetrad.sem that return types with arguments of type NodeModifier and TypeMethodDescriptioncliques.GeneralizedSemPm.getErrorNodes()Returns the list of exogenous variableNodes.StandardizedSemIm.getErrorNodes()getErrorNodes.SemPm.getLatentNodes()getLatentNodes.ReidentifyVariables.getLatents(Graph graph) getLatents.DagScorer.getMeasuredNodes()getMeasuredNodes.GeneralizedSemPm.getMeasuredNodes()Returns a list of measured nodes.ISemIm.getMeasuredNodes()getMeasuredNodes.Scorer.getMeasuredNodes()getMeasuredNodes.SemIm.getMeasuredNodes()The list of measured nodes for the semPm.SemPm.getMeasuredNodes()getMeasuredNodes.StandardizedSemIm.getMeasuredNodes()The list of measured nodes for the semPm.GeneralizedSemPm.getNodes()Retrieves a list of nodes.SemEvidence.getNodesInEvidence()getNodesInEvidence.GeneralizedSemPm.getParents(Node node) Retrieves the list of parent nodes for the given node.GeneralizedSemPm.getReferencedNodes(Node node) Retrieves a set of referenced nodes for the given node.GeneralizedSemPm.getReferencingNodes(Node node) Retrieves the set of referencing nodes for a given node.GeneralizedSemPm.getReferencingNodes(String parameter) Returns a set of nodes that reference the given parameter.GeneralizedSemPm.getVariableNodes()Returns the list of variable nodes--that is, node that is not error nodes.ISemIm.getVariableNodes()getVariableNodes.LargeScaleSimulation.getVariableNodes()Getter for the fieldvariableNodes.SemIm.getVariableNodes()The list of measured and latent nodes for the semPm.SemPm.getVariableNodes()Getter for the fieldvariableNodes.StandardizedSemIm.getVariableNodes()getVariableNodes.DagScorer.getVariables()Getter for the fieldvariables.Scorer.getVariables()getVariables.ISemIm.listUnmeasuredLatents()listUnmeasuredLatents.SemIm.listUnmeasuredLatents()listUnmeasuredLatents.Methods in edu.cmu.tetrad.sem with parameters of type NodeModifier and TypeMethodDescriptionbooleanSemIm.existsEdgeCoef(Node x, Node y) existsEdgeCoef.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) getCoefficientParameter.StandardizedSemIm.getCoefficientRange(Node a, Node b) getCoefficientRange.SemPm.getCovarianceParameter(Node nodeA, Node nodeB) getCovarianceParameter.StandardizedSemIm.getCovarianceRange(Node a, Node b) getCovarianceRange.doubleSemIm.getEdgeCoef(Node x, Node y) Getter for the fieldedgeCoef.doubleStandardizedSemIm.getEdgeCoef(Node a, Node b) Getter for the fieldedgeCoef.doubleSemIm.getErrCovar(Node x, Node y) Getter for the fielderrCovar.doubleStandardizedSemIm.getErrorCovariance(Node a, Node b) getErrorCovariance.GeneralizedSemPm.getErrorNode(Node node) Retrieves the error node associated with the given node.doubleStandardizedSemIm.getErrorVariance(Node error) getErrorVariance.doublegetErrVar.doubleISemIm.getIntercept(Node node) getIntercept.doubleSemIm.getIntercept(Node node) Calculates the intercept for a given node.doublegetMean.doubleCalculates the mean value associated with a givenNode.SemPm.getMeanParameter(Node node) getMeanParameter.doubleISemIm.getMeanStdDev(Node node) getMeanStdDev.doubleSemIm.getMeanStdDev(Node node) Calculates the mean standard deviation for the given node.GeneralizedSemPm.getNodeExpression(Node node) getNodeExpression.GeneralizedSemPm.getNodeExpressionString(Node node) getNodeExpressionString.intSemEvidence.getNodeIndex(Node node) getNodeIndex.GeneralizedSemIm.getNodeSubstitutedString(Node node) Retrieves the substituted string representation of a given Node.GeneralizedSemIm.getNodeSubstitutedString(Node node, Map<String, Double> substitutedValues) Retrieves the substituted string representation of a given Node.SemPm.getParameter(Node nodeA, Node nodeB) getParameter.doubleISemIm.getParamValue(Node nodeA, Node nodeB) getParamValue.doubleSemIm.getParamValue(Node nodeA, Node nodeB) getParamValue.GeneralizedSemPm.getParents(Node node) Retrieves the list of parent nodes for the given node.GeneralizedSemPm.getReferencedNodes(Node node) Retrieves a set of referenced nodes for the given node.GeneralizedSemPm.getReferencedParameters(Node node) Retrieves the set of referenced parameters from a given node.GeneralizedSemPm.getReferencingNodes(Node node) Retrieves the set of referencing nodes for a given node.doublegetStdDev.doublegetStdDev.doubleSemIm.getTotalEffect(Node x, Node y) Calculates the total effect between two nodes.doubleRetrieves the value associated with the given node.doubleISemIm.getVariance(Node nodeA, Matrix implCovar) getVariance.doubleSemIm.getVariance(Node node, Matrix implCovar) Returns the variance for a given node.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) setEdgeCoef.voidSemIm.setEdgeCoef(Node x, Node y, double value) Sets the coefficient value for the edge between two nodes in the graph.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) Setter for the fielderrCovar.voidSemIm.setErrCovar(Node x, Node y, double value) Setter for the fielderrCovar.booleanStandardizedSemIm.setErrorCovariance(Node a, Node b, double covar) Sets the covariance for the a<->b edge to the given covariance, if within range.voidsetErrVar.voidSets the error variance value for a specific node in the model's structural equation.voidISemIm.setIntercept(Node y, double intercept) setIntercept.voidSemIm.setIntercept(Node node, double intercept) Sets the intercept for a specified node in the SEM model.voidsetMean.voidSets the mean value for a given node in the variableNodes list.voidSemIm.setMeanStandardDeviation(Node node, double mean) Sets the mean associated with the given node.voidGeneralizedSemPm.setNodeExpression(Node node, String expressionString) Sets the expression for a given node.voidISemIm.setParamValue(Node nodeA, Node nodeB, double value) setParamValue.voidSemIm.setParamValue(Node nodeA, Node nodeB, double value) setParamValue.voidSets the value for a given node in the SemProposition object.Method parameters in edu.cmu.tetrad.sem with type arguments of type NodeModifier and TypeMethodDescriptionSemIm.getImplCovar(List<Node> nodes) Getter for the fieldimplCovar.ReidentifyVariables.reidentifyVariables1(List<List<Node>> partition, Graph trueGraph) reidentifyVariables1.reidentifyVariables2.Constructors in edu.cmu.tetrad.sem with parameters of type NodeModifierConstructorDescriptionEmpiricalDistributionForExpression(GeneralizedSemPm semPm, Node error, Context context) Constructor for EmpiricalDistributionForExpression.Constructor for Parameter.Constructor parameters in edu.cmu.tetrad.sem with type arguments 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) getAllParents.Method parameters in edu.cmu.tetrad.simulation with type arguments of type NodeModifier and TypeMethodDescriptionstatic GraphevalEdges.HsimUtils.getAllParents(Graph inputgraph, Set<Node> inputnodes) getAllParents.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) parseJSONObjectToTetradNode.Methods in edu.cmu.tetrad.util that return types with arguments of type NodeModifier and TypeMethodDescriptionJsonUtils.parseJSONArrayToTetradNodes(org.json.JSONArray jArray) parseJSONArrayToTetradNodes.DataConvertUtils.toNodes(DataColumn[] columns) toNodes.DataConvertUtils.toNodes(DiscreteDataColumn[] columns) toNodes.toNodes. -
Uses of Node in edu.pitt.csb.mgm
Methods in edu.pitt.csb.mgm that return types with arguments of type NodeModifier and TypeMethodDescriptionIndTestMultinomialLogisticRegressionWald.getVariables()getVariables.Methods in edu.pitt.csb.mgm with parameters of type NodeModifier and TypeMethodDescriptionIndTestMultinomialLogisticRegressionWald.checkIndependence(Node x, Node y, Set<Node> z) Determines the independence between two variables given a set of conditioning variables.booleanIndTestMultinomialLogisticRegressionWald.determines(List<Node> z, Node y) Determines the independence between a set of variables and a target variable.MixedUtils.getEdgeParams(Node n1, Node n2, GeneralizedSemPm pm) getEdgeParams.Method parameters in edu.pitt.csb.mgm with type arguments of type NodeModifier and TypeMethodDescriptionIndTestMultinomialLogisticRegressionWald.checkIndependence(Node x, Node y, Set<Node> z) Determines the independence between two variables given a set of conditioning variables.booleanIndTestMultinomialLogisticRegressionWald.determines(List<Node> z, Node y) Determines the independence between a set of variables and a target variable.static int[]MixedUtils.getContinuousInds(List<Node> nodes) getContinuousInds.static int[]MixedUtils.getDiscreteInds(List<Node> nodes) getDiscreteInds.IndTestMultinomialLogisticRegressionWald.indTestSubset(List<Node> vars) Tests the conditional independence between two variables given a sublist of variables.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) totalInstabilityDir.static double[]StabilityUtils.totalInstabilityUndir(cern.colt.matrix.DoubleMatrix2D xi, List<Node> vars) totalInstabilityUndir.