Uses of Enum Class
edu.cmu.tetrad.search.ConditioningSetType

Packages that use ConditioningSetType

Package	Description
edu.cmu.tetrad.algcomparison.statistic
edu.cmu.tetrad.algcomparison.sweep
edu.cmu.tetrad.search	This package contains classes for causal graph search algorithms.
edu.cmu.tetrad.search.harness

Uses of ConditioningSetType in edu.cmu.tetrad.algcomparison.statistic

Constructors in edu.cmu.tetrad.algcomparison.statistic with parameters of type ConditioningSetType

Modifier	Constructor	Description
	MarkovCheckAdPasses(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckAdPassesBestOf10(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckAndersonDarlingP(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckAndersonDarlingPBestOf10(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckBinomialP(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckBinomialPBestOf10(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType)	Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckFdrCutoffP(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckFractionDependentH0(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckFractionDependentH1(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Anderson Darling P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckKolmogorovSmirnoffP(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckKolmogorovSmirnoffPBestOf10(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckKsPasses(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	MarkovCheckKsPassesBestOf10(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the Kolmogorov-Smirnoff P value for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	McGetNumTestsH0(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the number of tests for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).
	McGetNumTestsH1(IndependenceWrapper independenceWrapper, ConditioningSetType conditioningSetType, Parameters mcParameters)	Calculates the number of tests for the Markov check of whether the p-values for the estimated graph are distributed as U(0, 1).

Uses of ConditioningSetType in edu.cmu.tetrad.algcomparison.sweep

Methods in edu.cmu.tetrad.algcomparison.sweep with parameters of type ConditioningSetType

Modifier and Type	Method	Description
void	ParameterSweep.setConditioningSetType(ConditioningSetType conditioningSetType)	Sets the conditioning set type for the Markov check.

Uses of ConditioningSetType in edu.cmu.tetrad.search

Subclasses with type arguments of type ConditioningSetType in edu.cmu.tetrad.search

Modifier and Type	Class	Description
enum	ConditioningSetType	The type of conditioning set to use for the Markov check.

Methods in edu.cmu.tetrad.search that return ConditioningSetType

Modifier and Type	Method	Description
ConditioningSetType	MarkovCheck.getSetType()	Returns type of conditioning sets to use in the Markov check.
static ConditioningSetType	ConditioningSetType.valueOf(String name)	Returns the enum constant of this class with the specified name.
static ConditioningSetType[]	ConditioningSetType.values()	Returns an array containing the constants of this enum class, in the order they are declared.

Methods in edu.cmu.tetrad.search with parameters of type ConditioningSetType

Modifier and Type	Method	Description
static List<IndependenceResult>	MarkovAuditUtils.auditFailures(Graph graph, IndependenceTest test, ConditioningSetType setType, double q, boolean negativelyCorrelated)	Runs a Markov audit of graph against test and returns the implied independence facts rejected under Benjamini-Hochberg at level q -- NOT the raw per-test rejections.
static List<IndependenceResult>	MarkovAuditUtils.auditFailures(Graph graph, IndependenceTest test, ConditioningSetType setType, double q, boolean negativelyCorrelated, Fas.DeterminismGuard guard)	Audits a given graph for independence test failures and applies false discovery rate (FDR) correction at a specified level to return only significant failures.
static MarkovCheckNullReference.Result	MarkovCheckNullReference.compute(DataSet data, Graph graph, IndependenceWrapper testWrapper, Parameters parameters, ConditioningSetType conditioningSetType, MarkovCheckNullReference.SimulatorType simulator, int numDraws, int sampleSize, long baseSeed, TrainedDagSimulatorGNM.Params gnmParams)	Convenience overload taking an IndependenceWrapper and Parameters, matching how the Markov-check test is configured in algcomparison and in py-tetrad's TetradSearch.
static MarkovCheckNullReference.Result	MarkovCheckNullReference.compute(DataSet data, Graph graph, Function<DataSet, IndependenceTest> testFactory, ConditioningSetType conditioningSetType, MarkovCheckNullReference.SimulatorType simulator, int numDraws, int sampleSize, long baseSeed, TrainedDagSimulatorGNM.Params gnmParams)	Computes the null reference using a test factory.
static Set<IndependenceFact>	MarkovCheck.computeAllImpliedFacts(Graph g, ConditioningSetType setType)	Computes all implied independence facts for the given graph based on the specified conditioning set type.
static Map<String, List<IndependenceFact>>	MarkovCheck.computeImpliedFactsByVertex(Graph graph, ConditioningSetType setType)	Computes the implied independence facts for EVERY vertex of graph at once, keyed by vertex name.
static List<IndependenceFact>	MarkovCheck.computeImpliedFactsForVertex(Graph graph, Node x, ConditioningSetType conditioningSetType)	Computes the implied independence facts for a given vertex within the specified graph based on the provided conditioning set type.
static List<IndependenceFact>	MarkovCheck.computeImpliedFactsForVertex(Graph graph, Node x, ConditioningSetType conditioningSetType, Graph preparedMag)	Variant of MarkovCheck.computeImpliedFactsForVertex(Graph, Node, ConditioningSetType) accepting a MAG prepared once per graph by MarkovCheck.prepareMagForVertexFacts(Graph, ConditioningSetType).
List<Double>	MarkovCheck.getPrecisionAndRecallGraphPlotData(Node x, Graph estimatedGraph, Graph trueGraph, ConditioningSetType conditioningSetType, String subgraphFeature)	Computes the precision and recall values for a specified subgraph structure between an estimated graph and a true graph.
static Set<Node>	MarkovAuditUtils.implicatedVertices(Graph graph, IndependenceTest test, ConditioningSetType setType, double q, boolean negativelyCorrelated)	Identifies and returns the set of vertices implicated by audit failures of a graph based on the provided independence test, conditioning set type, false discovery rate (FDR) level, and correlation constraints.
static Graph	MarkovCheck.prepareMagForVertexFacts(Graph graph, ConditioningSetType setType)	Precomputes the graph-level transform (the MAG) used by the ordered-local-Markov conditioning types, so that callers evaluating facts for many vertices of the same graph can run the graph-type legality checks and the CPDAG-to-DAG-to-MAG conversion once rather than once per vertex.
void	MarkovCheck.setSetType(ConditioningSetType setType)	Sets the type of conditioning sets to use in the Markov check.

Constructors in edu.cmu.tetrad.search with parameters of type ConditioningSetType

Modifier	Constructor	Description
	MarkovCheck(Graph graph, IndependenceTest independenceTest, ConditioningSetType setType)	Constructor.
	VertexRepairSearch(Graph graph, IndependenceTest test, ConditioningSetType type)	Constructs a new instance of VertexRepairSearch.

Uses of ConditioningSetType in edu.cmu.tetrad.search.harness

Methods in edu.cmu.tetrad.search.harness with parameters of type ConditioningSetType

Modifier and Type	Method	Description
void	GraphoidClosureHarness.run(Graph graph, IndependenceTest test, ConditioningSetType conditioningSetType, GraphoidClosureHarness.ClosureType closureType)	Runs the harness.