Uses of Interface
edu.cmu.tetrad.data.DataModel

Packages that use DataModel

Package	Description
edu.cmu.tetrad.algcomparison
edu.cmu.tetrad.algcomparison.algorithm
edu.cmu.tetrad.algcomparison.algorithm.cluster
edu.cmu.tetrad.algcomparison.algorithm.continuous.dag
edu.cmu.tetrad.algcomparison.algorithm.external
edu.cmu.tetrad.algcomparison.algorithm.mixed
edu.cmu.tetrad.algcomparison.algorithm.multi
edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
edu.cmu.tetrad.algcomparison.algorithm.other
edu.cmu.tetrad.algcomparison.algorithm.pairwise
edu.cmu.tetrad.algcomparison.independence
edu.cmu.tetrad.algcomparison.score
edu.cmu.tetrad.algcomparison.simulation
edu.cmu.tetrad.algcomparison.statistic
edu.cmu.tetrad.bayes
edu.cmu.tetrad.data
edu.cmu.tetrad.data.simulation
edu.cmu.tetrad.search	Contains classes for searching for (mostly structural) causal models given data.
edu.cmu.tetrad.search.score	Contains classes for various sorts of scores for running score-based algorithms.
edu.cmu.tetrad.search.test	Contains classes for running conditional independence tests for various sorts of data.
edu.cmu.tetrad.search.utils	Contains some utility classes for search algorithms.
edu.cmu.tetrad.search.work_in_progress	Contains some classes that aren't ready for prime time.
edu.cmu.tetrad.util
edu.pitt.dbmi.algo.resampling.task

Uses of DataModel in edu.cmu.tetrad.algcomparison

Methods in edu.cmu.tetrad.algcomparison with parameters of type DataModel

Modifier and Type	Method	Description
static String	CompareTwoGraphs.getStatsListTable(Graph trueGraph, Graph targetGraph, DataModel dataModel, long elapsedTime)	Returns a string representing a table of statistics that can be printed.

Uses of DataModel in edu.cmu.tetrad.algcomparison.algorithm

Methods in edu.cmu.tetrad.algcomparison.algorithm with parameters of type DataModel

Modifier and Type	Method	Description
abstract long	ExternalAlgorithm.getElapsedTime(DataModel dataSet, Parameters parameters)	getElapsedTime.
int	ExternalAlgorithm.getIndex(DataModel dataSet)	getIndex.
Graph	Algorithm.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	FirstInflection.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	StabilitySelection.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	StARS.search(DataModel dataSet, Parameters parameters)	Runs the search.

Method parameters in edu.cmu.tetrad.algcomparison.algorithm with type arguments of type DataModel

Modifier and Type	Method	Description
Graph	MultiDataSetAlgorithm.search(List<DataModel> dataSets, Parameters parameters)	Runs the search.

Uses of DataModel in edu.cmu.tetrad.algcomparison.algorithm.cluster

Methods in edu.cmu.tetrad.algcomparison.algorithm.cluster with parameters of type DataModel

Modifier and Type	Method	Description
Graph	Bpc.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Fofc.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Ftfc.search(DataModel dataSet, Parameters parameters)	Runs the search.

Uses of DataModel in edu.cmu.tetrad.algcomparison.algorithm.continuous.dag

Methods in edu.cmu.tetrad.algcomparison.algorithm.continuous.dag with parameters of type DataModel

Modifier and Type	Method	Description
Graph	Dagma.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	DirectLingam.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	IcaLingam.search(DataModel dataSet, Parameters parameters)	Searches for a graph structure based on the given data set and parameters.
Graph	IcaLingD.search(DataModel dataSet, Parameters parameters)	Runs a search on the provided data set using the given parameters.

Uses of DataModel in edu.cmu.tetrad.algcomparison.algorithm.external

Methods in edu.cmu.tetrad.algcomparison.algorithm.external with parameters of type DataModel

Modifier and Type	Method	Description
long	ExternalAlgorithmBnlearnMmhc.getElapsedTime(DataModel dataSet, Parameters parameters)	getElapsedTime.
long	ExternalAlgorithmBNTPc.getElapsedTime(DataModel dataSet, Parameters parameters)	getElapsedTime.
long	ExternalAlgorithmIntersection.getElapsedTime(DataModel dataSet, Parameters parameters)	getElapsedTime.
long	ExternalAlgorithmPcalgGes.getElapsedTime(DataModel dataSet, Parameters parameters)	getElapsedTime.
long	ExternalAlgorithmPcalgPc.getElapsedTime(DataModel dataSet, Parameters parameters)	getElapsedTime.
long	ExternalAlgorithmTetrad.getElapsedTime(DataModel dataSet, Parameters parameters)	getElapsedTime.
Graph	ExternalAlgorithmBnlearnMmhc.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	ExternalAlgorithmBNTPc.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	ExternalAlgorithmIntersection.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	ExternalAlgorithmPcalgGes.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	ExternalAlgorithmPcalgPc.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	ExternalAlgorithmTetrad.search(DataModel dataSet, Parameters parameters)	Runs the search.

Uses of DataModel in edu.cmu.tetrad.algcomparison.algorithm.mixed

Methods in edu.cmu.tetrad.algcomparison.algorithm.mixed with parameters of type DataModel

Modifier and Type	Method	Description
Graph	Mgm.search(DataModel ds, Parameters parameters)	Runs the search.

Uses of DataModel in edu.cmu.tetrad.algcomparison.algorithm.multi

Methods in edu.cmu.tetrad.algcomparison.algorithm.multi with parameters of type DataModel

Modifier and Type	Method	Description
Graph	Fask.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	FaskConcatenated.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	FaskLofsConcatenated.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	FaskVote.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	FasLofs.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	FciIod.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	FgesConcatenated.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Images.search(DataModel dataSet, Parameters parameters)	Searches for a graph based on the given data set and parameters.
Graph	ImagesBoss.search(DataModel dataSet, Parameters parameters)	Runs the search.

Method parameters in edu.cmu.tetrad.algcomparison.algorithm.multi with type arguments of type DataModel

Modifier and Type	Method	Description
Graph	FaskConcatenated.search(List<DataModel> dataSets, Parameters parameters)	Runs the search.
Graph	FaskLofsConcatenated.search(List<DataModel> dataModels, Parameters parameters)	Runs the search.
Graph	FaskVote.search(List<DataModel> dataSets, Parameters parameters)	Runs the search.
Graph	FciIod.search(List<DataModel> dataSets, Parameters parameters)	Runs the search.
Graph	FgesConcatenated.search(List<DataModel> dataModels, Parameters parameters)	Runs the search.
Graph	Images.search(List<DataModel> dataSets, Parameters parameters)	Searches for a graph based on the given data sets and parameters.
Graph	ImagesBoss.search(List<DataModel> dataSets, Parameters parameters)	Runs the search.

Uses of DataModel in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag

Methods in edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag with parameters of type DataModel

Modifier and Type	Method	Description
Graph	Boss.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	BossLingam.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	Cpc.search(DataModel dataModel, Parameters parameters)	Searches for a graph based on the given data model and parameters.
Graph	Cstar.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Fas.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Fges.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	FgesMb.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	FgesMeasurement.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	GesMe.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Grasp.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	Pc.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	Pcd.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	PcMb.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	RestrictedBoss.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	SingleGraphAlg.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Sp.search(DataModel dataModel, Parameters parameters)	Runs the search.

Uses of DataModel in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag

Methods in edu.cmu.tetrad.algcomparison.algorithm.oracle.pag with parameters of type DataModel

Modifier and Type	Method	Description
Graph	Bfci.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	Ccd.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Cfci.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	Fci.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	FciMax.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	Gfci.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	GraspFci.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	PagSampleRfci.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Rfci.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	RfciBsc.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	SpFci.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	SvarFci.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	SvarGfci.search(DataModel dataModel, Parameters parameters)	Runs the search.

Uses of DataModel in edu.cmu.tetrad.algcomparison.algorithm.other

Methods in edu.cmu.tetrad.algcomparison.algorithm.other with parameters of type DataModel

Modifier and Type	Method	Description
Graph	FactorAnalysis.search(DataModel ds, Parameters parameters)	Runs the search.
Graph	Glasso.search(DataModel ds, Parameters parameters)	Runs the search.

Uses of DataModel in edu.cmu.tetrad.algcomparison.algorithm.pairwise

Methods in edu.cmu.tetrad.algcomparison.algorithm.pairwise with parameters of type DataModel

Modifier and Type	Method	Description
Graph	Eb.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	FaskPw.search(DataModel dataModel, Parameters parameters)	Runs the search.
Graph	R1.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	R2.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	R3.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Rskew.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	RskewE.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Skew.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	SkewE.search(DataModel dataSet, Parameters parameters)	Runs the search.
Graph	Tanh.search(DataModel dataSet, Parameters parameters)	Runs the search.

Uses of DataModel in edu.cmu.tetrad.algcomparison.independence

Methods in edu.cmu.tetrad.algcomparison.independence with parameters of type DataModel

Modifier and Type	Method	Description
IndependenceTest	BdeuTest.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	CciTest.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	ChiSquare.getTest(DataModel dataSet, Parameters parameters)	Retrieves an instance of the IndependenceTest interface for the Chi Square Test.
IndependenceTest	ConditionalGaussianLRT.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	DegenerateGaussianLRT.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	DiscreteBicTest.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	FisherZ.getTest(DataModel dataModel, Parameters parameters)	Retrieves an IndependenceTest object based on the given data model and parameters.
IndependenceTest	GICScoreTests.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	GSquare.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	IndependenceWrapper.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	Kci.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	MagSemBicTest.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	Mnlrlrt.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	MSeparationTest.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	MultinomialLogisticRegressionWald.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	Mvplrt.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	PositiveCorr.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	ProbabilisticTest.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	SemBicDTest.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
IndependenceTest	SemBicTest.getTest(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.

Uses of DataModel in edu.cmu.tetrad.algcomparison.score

Methods in edu.cmu.tetrad.algcomparison.score with parameters of type DataModel

Modifier and Type	Method	Description
Score	BdeuScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	ConditionalGaussianBicScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	DegenerateGaussianBicScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	DiscreteBicScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	EbicScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	FisherZScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	GicScores.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	MagSemBicScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	MSeparationScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	MVPBicScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	PoissonPriorScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	PositiveCorrScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	ScoreWrapper.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	SemBicScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	SemBicScoreDeterministic.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.
Score	ZhangShenBoundScore.getScore(DataModel dataSet, Parameters parameters)	Returns true iff x and y are independent conditional on z for the given data set.

Uses of DataModel in edu.cmu.tetrad.algcomparison.simulation

Methods in edu.cmu.tetrad.algcomparison.simulation that return DataModel

Modifier and Type	Method	Description
DataModel	BayesNetSimulation.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	ConditionalGaussianSimulation.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	GeneralSemSimulation.getDataModel(int index)	Returns the data model at the specified index.
DataModel	GeneralSemSimulationSpecial1.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	LeeHastieSimulation.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	LinearFisherModel.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	LinearSineSimulation.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	NLSemSimulation.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	SemSimulation.getDataModel(int index)	Returns the data model at the specified index.
DataModel	SemThenDiscretize.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	Simulation.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	StandardizedSemSimulation.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	TimeSeriesSemSimulation.getDataModel(int index)	Returns the number of data sets to simulate.

Constructor parameters in edu.cmu.tetrad.algcomparison.simulation with type arguments of type DataModel

Modifier	Constructor	Description
	LinearFisherModel(RandomGraph graph, List<DataModel> shocks)	Constructor for LinearFisherModel.

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

Methods in edu.cmu.tetrad.algcomparison.statistic with parameters of type DataModel

Modifier and Type	Method	Description
double	AdjacencyFn.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AdjacencyFp.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AdjacencyFpr.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AdjacencyPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AdjacencyRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AdjacencyTn.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AdjacencyTp.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AdjacencyTpr.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AncestorF1.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AncestorPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AncestorRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AncestralPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AncestralRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ArrowheadFn.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ArrowheadFp.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ArrowheadFpr.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ArrowheadPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ArrowheadPrecisionCommonEdges.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ArrowheadRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ArrowheadRecallCommonEdges.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ArrowheadTn.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ArrowheadTp.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AverageDegreeEst.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	AverageDegreeTrue.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	BicDiff.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	BicDiffPerRecord.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	BicEst.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	BicTrue.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	BidirectedEst.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	BidirectedFP.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	BidirectedLatentPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	BidirectedPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	BidirectedRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	BidirectedTP.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	BidirectedTrue.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	CommonAncestorFalseNegativeBidirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	CommonAncestorFalsePositiveBidirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	CommonAncestorTruePositiveBidirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	CommonMeasuredAncestorRecallBidirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	CorrectSkeleton.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	DefiniteDirectedPathPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	DefiniteDirectedPathRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	DensityEst.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	DensityTrue.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ElapsedCpuTime.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	F1Adj.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	F1All.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	F1Arrow.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	FalseNegativesAdjacencies.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	FalsePositiveAdjacencies.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	FBetaAdj.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	FractionDependentUnderAlternative.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	FractionDependentUnderNull.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	GraphExactlyRight.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	LatentCommonAncestorFalseNegativeBidirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	LatentCommonAncestorFalsePositiveBidirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	LatentCommonAncestorRecallBidirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	LatentCommonAncestorTruePositiveBidirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	LegalPag.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	MathewsCorrAdj.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	MathewsCorrArrow.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	MaximalityCondition.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NoAlmostCyclicPathsCondition.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NoAlmostCyclicPathsInMagCondition.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NoCyclicPathsCondition.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NoCyclicPathsInMagCondition.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NodesInCyclesPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NodesInCyclesRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NonancestorPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NonancestorRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NoSemidirectedF1.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NoSemidirectedPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NoSemidirectedRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumAmbiguousTriples.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumberOfEdgesEst.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumberOfEdgesTrue.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumBidirectedBothNonancestorAncestor.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumBidirectedEdgesEst.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumBidirectedEdgesTrue.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumColoredDD.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumColoredNL.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumColoredPD.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumColoredPL.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCommonMeasuredAncestorBidirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCompatibleDefiniteDirectedEdgeAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCompatibleDirectedEdgeConfounded.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCompatibleDirectedEdgeNonAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCompatibleEdges.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCompatiblePossiblyDirectedEdgeAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCompatiblePossiblyDirectedEdgeNonAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCompatibleVisibleAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCompatibleVisibleNonancestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCorrectDDAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCorrectPDAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumCorrectVisibleAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDefinitelyDirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDefinitelyNotDirectedPaths.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDirectedEdgeAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDirectedEdgeBnaMeasuredCounfounded.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDirectedEdgeNoMeasureAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDirectedEdgeNotAncNotRev.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDirectedEdgeReversed.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDirectedEdges.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDirectedEdgeVisible.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDirectedPathsEst.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDirectedPathsTrue.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumDirectedShouldBePartiallyDirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumIncorrectDDAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumIncorrectPDAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumIncorrectVisibleAncestors.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumLatentCommonAncestorBidirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumNondirectedEdges.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumParametersEst.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumPartiallyOrientedEdges.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumPossiblyDirected.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumUndirectedEdges.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	NumVisibleEst.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	OrientationPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	OrientationRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	PagAdjacencyPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	PagAdjacencyRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ParameterColumn.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	PercentAmbiguous.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	PercentBidirectedEdges.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ProportionSemidirectedPathsNotReversedEst.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	ProportionSemidirectedPathsNotReversedTrue.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	PvalueDistanceToAlpha.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	PvalueUniformityUnderNull.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	SemidirectedPathF1.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	SemidirectedPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	SemidirectedRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	Statistic.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	StructuralHammingDistance.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TailPrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TailRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TrueDagFalseNegativesArrows.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TrueDagFalseNegativesTails.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TrueDagFalsePositiveArrow.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TrueDagFalsePositiveTails.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TrueDagPrecisionArrow.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TrueDagPrecisionTails.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TrueDagRecallArrows.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TrueDagRecallTails.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TrueDagTruePositiveArrow.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TrueDagTruePositiveDirectedPathNonancestor.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TrueDagTruePositiveTails.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TwoCycleFalseNegative.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TwoCycleFalsePositive.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TwoCyclePrecision.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TwoCycleRecall.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
double	TwoCycleTruePositive.getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.

Uses of DataModel in edu.cmu.tetrad.bayes

Constructors in edu.cmu.tetrad.bayes with parameters of type DataModel

Modifier	Constructor	Description
	JunctionTreeAlgorithm(Graph graph, DataModel dataModel)	Constructor for JunctionTreeAlgorithm.

Uses of DataModel in edu.cmu.tetrad.data

Subinterfaces of DataModel in edu.cmu.tetrad.data

Modifier and Type	Interface	Description
interface	DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
interface	ICovarianceMatrix	Interface for covariance matrices.

Classes in edu.cmu.tetrad.data that implement DataModel

Modifier and Type	Class	Description
final class	BoxDataSet	Wraps a DataBox in such a way that mixed data sets can be stored.
final class	CorrelationMatrix	Stores a correlation matrix together with variable names and sample size; intended as a representation of a data set.
class	CorrelationMatrixOnTheFly	Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
class	CovarianceMatrix	Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
class	CovarianceMatrixOnTheFly	Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
final class	DataModelList	Stores a list of data models and keeps track of which one is selected.
class	IndependenceFacts	Stores a list of independence facts.
final class	NumberObjectDataSet	Wraps a 2D array of Number objects in such a way that mixed data sets can be stored.
final class	TimeSeriesData	Stores time series data as a list of continuous columns.

Methods in edu.cmu.tetrad.data that return DataModel

Modifier and Type	Method	Description
DataModel	CorrelationMatrixOnTheFly.copy()	copy.
DataModel	CovarianceMatrix.copy()	copy.
DataModel	CovarianceMatrixOnTheFly.copy()	copy.
DataModel	DataModel.copy()	copy.
DataModel	DataModelList.copy()	copy.
DataModel	IndependenceFacts.copy()	copy.
DataModel	TimeSeriesData.copy()	copy.
DataModel	DataModelList.get(int index)
DataModel	DataModelList.getSelectedModel()	Getter for the field selectedModel.
DataModel	DataModelList.remove(int index)

Methods in edu.cmu.tetrad.data that return types with arguments of type DataModel

Modifier and Type	Method	Description
List<DataModel>	DataModelList.getModelList()	Getter for the field modelList.

Methods in edu.cmu.tetrad.data with parameters of type DataModel

Modifier and Type	Method	Description
void	DataModelList.add(int index, DataModel element)	Adds the given DataModel to the list at the given index.
static DataSet	SimpleDataLoader.getContinuousDataSet(DataModel dataSet)	Returns the datamodel case to DataSet if it is continuous.
static ICovarianceMatrix	SimpleDataLoader.getCovarianceMatrix(DataModel dataModel, boolean precomputeCovariances)	Returns the model cast to ICovarianceMatrix if already a covariance matric, or else returns the covariance matrix for a dataset.
static DataSet	SimpleDataLoader.getDiscreteDataSet(DataModel dataSet)	Returns the datamodel case to DataSet if it is discrete.
static DataSet	SimpleDataLoader.getMixedDataSet(DataModel dataSet)	Returns the datamodel case to DataSet if it is mixed.
void	DataModelList.setSelectedModel(DataModel model)	Setter for the field selectedModel.

Uses of DataModel in edu.cmu.tetrad.data.simulation

Methods in edu.cmu.tetrad.data.simulation that return DataModel

Modifier and Type	Method	Description
DataModel	LoadContinuousDataAndGraphs.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	LoadContinuousDataAndSingleGraph.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	LoadContinuousDataSmithSim.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	LoadDataAndGraphs.getDataModel(int index)	Returns the number of data sets to simulate.
DataModel	LoadDataFromFileWithoutGraph.getDataModel(int index)	Returns the number of data sets to simulate.

Uses of DataModel in edu.cmu.tetrad.search

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

Modifier and Type	Method	Description
DataModel	CompositeIndependenceTest.getData()	getData.
DataModel	IndependenceTest.getData()	getData.

Uses of DataModel in edu.cmu.tetrad.search.score

Methods in edu.cmu.tetrad.search.score that return DataModel

Modifier and Type	Method	Description
DataModel	PoissonPriorScore.getData()	Returns the data set.
DataModel	SemBicScore.getData()	Returns the data model.
DataModel	SemBicScore.getDataModel()	Returns the data model.

Methods in edu.cmu.tetrad.search.score with parameters of type DataModel

Modifier and Type	Method	Description
static double	SemBicScorer.scoreDag(Graph dag, DataModel data, boolean precomputeCovariances)	Scores the given DAG using the given data model, usimg a BIC score.
static double	SemBicScorer.scoreDag(Graph dag, DataModel data, double penaltyDiscount, boolean precomputeCovariances)	Scores the given DAG using the given data model, usimg a BIC score.

Uses of DataModel in edu.cmu.tetrad.search.test

Methods in edu.cmu.tetrad.search.test that return DataModel

Modifier and Type	Method	Description
DataModel	IndTestIndependenceFacts.getData()	Returns the facts supplied in the constructor, which constutite a data model.
DataModel	IndTestProbabilistic.getData()	Returns the data model associated with this instance.
DataModel	Kci.getData()	Returns The data model for the independence test.
DataModel	ScoreIndTest.getData()	Retrieves the data model associated with this object.

Constructors in edu.cmu.tetrad.search.test with parameters of type DataModel

Modifier	Constructor	Description
	ScoreIndTest(Score score, DataModel data)	Constructor for ScoreIndTest.

Uses of DataModel in edu.cmu.tetrad.search.utils

Methods in edu.cmu.tetrad.search.utils with parameters of type DataModel

Modifier and Type	Method	Description
static void	LogUtilsSearch.stampWithBic(Graph graph, DataModel dataModel)	stampWithBic.

Constructors in edu.cmu.tetrad.search.utils with parameters of type DataModel

Modifier	Constructor	Description
	ClusterSignificance(List<Node> variables, DataModel dataModel)	Constructs a new cluster significance object.

Constructor parameters in edu.cmu.tetrad.search.utils with type arguments of type DataModel

Modifier	Constructor	Description
	ShiftSearch(List<DataModel> dataSets)	Constructor for ShiftSearch.

Uses of DataModel in edu.cmu.tetrad.search.work_in_progress

Methods in edu.cmu.tetrad.search.work_in_progress that return DataModel

Modifier and Type	Method	Description
DataModel	ProbabilisticMapIndependence.getData()	getData.

Uses of DataModel in edu.cmu.tetrad.util

Methods in edu.cmu.tetrad.util that return DataModel

Modifier and Type	Method	Description
static DataModel	MultidataUtils.combineDataset(List<DataModel> dataModels)	combineDataset.
static DataModel	DataConvertUtils.toContinuousDataModel(ContinuousData dataset)	toContinuousDataModel.
static DataModel	DataConvertUtils.toCovarianceMatrix(CovarianceData dataset)	toCovarianceMatrix.
static DataModel	DataConvertUtils.toDataModel(Data data)	toDataModel.
static DataModel	DataConvertUtils.toDataModel(Data data, Metadata metadata)	toDataModel.
static DataModel	DataConvertUtils.toMixedDataBox(MixedTabularData dataset)	toMixedDataBox.
static DataModel	DataConvertUtils.toMixedDataBox(MixedTabularData dataset, Metadata metadata)	Converting using metadata
static DataModel	DataConvertUtils.toVerticalDiscreteDataModel(VerticalDiscreteTabularData dataset)	toVerticalDiscreteDataModel.
static DataModel	DataConvertUtils.toVerticalDiscreteDataModel(VerticalDiscreteTabularData dataset, Metadata metatdata)	Converting using metadata

Methods in edu.cmu.tetrad.util with parameters of type DataModel

Modifier and Type	Method	Description
static int	MultidataUtils.getNumberOfColumns(DataModel dataModel)	getNumberOfColumns.

Method parameters in edu.cmu.tetrad.util with type arguments of type DataModel

Modifier and Type	Method	Description
static void	MultidataUtils.combineContinuousData(List<DataModel> dataModels, double[][] combinedData)	combineContinuousData.
static DataModel	MultidataUtils.combineDataset(List<DataModel> dataModels)	combineDataset.
static void	MultidataUtils.combineDiscreteDataToDiscreteVerticalData(List<DataModel> dataModels, List<Node> variables, int[][] combinedData, int numOfRows, int numOfColumns)	combineDiscreteDataToDiscreteVerticalData.
static void	MultidataUtils.combineMixedContinuousData(List<DataModel> dataModels, List<Node> variables, double[][] combinedData, int numOfRows, int numOfColumns)	combineMixedContinuousData.
static void	MultidataUtils.combineMixedDiscreteData(List<DataModel> dataModels, List<Node> variables, int[][] combinedData, int numOfRows, int numOfColumns)	combineMixedDiscreteData.
static void	MultidataUtils.combineVariables(List<DataModel> dataModels, List<Node> variables)	Combine the list of variables from each of data model in the list into one variable list.
static int[]	MultidataUtils.getRowCounts(List<DataModel> dataModels)	getRowCounts.

Uses of DataModel in edu.pitt.dbmi.algo.resampling.task

Constructors in edu.pitt.dbmi.algo.resampling.task with parameters of type DataModel

Modifier	Constructor	Description
	GeneralResamplingSearchRunnable(DataModel dataModel, Algorithm algorithm, Parameters parameters)	Constructor for single-data set algorithms.

Constructor parameters in edu.pitt.dbmi.algo.resampling.task with type arguments of type DataModel

Modifier	Constructor	Description
	GeneralResamplingSearchRunnable(List<DataModel> dataModel, MultiDataSetAlgorithm algorithm, Parameters parameters)	Constructor for multi-data set algorithms.