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

Packages that use ICovarianceMatrix

Package	Description
edu.cmu.tetrad.data
edu.cmu.tetrad.regression
edu.cmu.tetrad.search	Contains classes for searching for (mostly structural) causal models given data.
edu.cmu.tetrad.search.score	Contains classes for various 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.sem

Uses of ICovarianceMatrix in edu.cmu.tetrad.data

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

Modifier and Type	Class	Description
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.

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

Modifier and Type	Method	Description
static ICovarianceMatrix	DataTransforms.covarianceNonparanormalDrton(DataSet dataSet)
static @NotNull ICovarianceMatrix	SimpleDataLoader.getCorrelationMatrix(DataSet dataSet)
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 @NotNull ICovarianceMatrix	SimpleDataLoader.getCovarianceMatrix(DataSet dataSet, boolean precomputeCovariances)
final ICovarianceMatrix	CorrelationMatrixOnTheFly.getSubmatrix(int[] indices)
final ICovarianceMatrix	CorrelationMatrixOnTheFly.getSubmatrix(List<String> submatrixVarNames)
final ICovarianceMatrix	CovarianceMatrix.getSubmatrix(int[] indices)
final ICovarianceMatrix	CovarianceMatrix.getSubmatrix(List<String> submatrixVarNames)
final ICovarianceMatrix	CovarianceMatrixOnTheFly.getSubmatrix(int[] indices)
final ICovarianceMatrix	CovarianceMatrixOnTheFly.getSubmatrix(int[] indices, int[] dataRows)
final ICovarianceMatrix	CovarianceMatrixOnTheFly.getSubmatrix(List<String> submatrixVarNames)
ICovarianceMatrix	ICovarianceMatrix.getSubmatrix(int[] indices)
ICovarianceMatrix	ICovarianceMatrix.getSubmatrix(String[] submatrixVarNames)
ICovarianceMatrix	ICovarianceMatrix.getSubmatrix(List<String> submatrixVarNames)
static ICovarianceMatrix	SimpleDataLoader.loadCovarianceMatrix(char[] chars, String commentMarker, DelimiterType delimiterType, char quoteChar, String missingValueMarker)	Parses a covariance matrix from a char[] array.
static ICovarianceMatrix	SimpleDataLoader.loadCovarianceMatrix(File file, String commentMarker, DelimiterType delimiter, char quoteCharacter, String missingValueMarker)	Parses the given files for a tabular data set, returning a RectangularDataSet if successful.
static ICovarianceMatrix	CorrelationMatrixOnTheFly.serializableInstance()	Generates a simple exemplar of this class to test serialization.
static ICovarianceMatrix	CovarianceMatrix.serializableInstance()	Generates a simple exemplar of this class to test serialization.
static ICovarianceMatrix	CovarianceMatrixOnTheFly.serializableInstance()	Generates a simple exemplar of this class to test serialization.

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

Modifier and Type	Method	Description
static double	DataUtils.getEss(ICovarianceMatrix covariances)	Returns the equivalent sample size, assuming all units are equally correlated and all unit variances are equal.
static List<Node>	DataUtils.getExampleNonsingular(ICovarianceMatrix covarianceMatrix, int depth)
static Matrix	DataUtils.subMatrix(ICovarianceMatrix m, Node x, Node y, List<Node> z)
static Matrix	DataUtils.subMatrix(ICovarianceMatrix m, Map<Node,Integer> indexMap, Node x, Node y, List<Node> z)
static void	DataWriter.writeCovMatrix(ICovarianceMatrix covMatrix, PrintWriter out, NumberFormat nf)	Writes the lower triangle of a covariance matrix to file.

Constructors in edu.cmu.tetrad.data with parameters of type ICovarianceMatrix

Modifier	Constructor	Description
	CorrelationMatrix(ICovarianceMatrix matrix)	Constructs a new correlation matrix using the covariances in the given covariance matrix.
	CorrelationMatrixOnTheFly(ICovarianceMatrix cov)	Constructs a new covariance matrix from the given data set.
	CovarianceMatrix(ICovarianceMatrix covMatrix)

Uses of ICovarianceMatrix in edu.cmu.tetrad.regression

Constructors in edu.cmu.tetrad.regression with parameters of type ICovarianceMatrix

Modifier	Constructor	Description
	RegressionCovariance(ICovarianceMatrix covariances)	Constructs a covariance-based regression model using the given covariance matrix, assuming that no means are specified.

Uses of ICovarianceMatrix in edu.cmu.tetrad.search

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

Modifier and Type	Method	Description
default ICovarianceMatrix	IndependenceTest.getCov()	Returns the covariance matrix.
ICovarianceMatrix	Bpc.getCovarianceMatrix()	Returns the wrapped covariance matrix.
ICovarianceMatrix	Mimbuild.getLatentsCov()	Returns the inferred covariance matrix over the latent variables.
ICovarianceMatrix	MimbuildTrek.getLatentsCov()	The covariance matrix over the latents that is implied by the clustering.

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

Modifier and Type	Method	Description
Graph	Mimbuild.search(List<List<Node>> clustering, List<String> latentNames, ICovarianceMatrix measuresCov)	Does a Mimbuild search.
Graph	MimbuildTrek.search(List<List<Node>> clustering, List<String> latentNames, ICovarianceMatrix measuresCov)	Does the search and returns the graph.

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

Modifier	Constructor	Description
	Bpc(ICovarianceMatrix covarianceMatrix, double alpha, BpcTestType sigTestType)	Constructor.
	FactorAnalysis(ICovarianceMatrix covarianceMatrix)	Constructor.
	Fofc(ICovarianceMatrix cov, BpcTestType testType, Fofc.Algorithm algorithm, double alpha)	Constructor.
	Ftfc(ICovarianceMatrix cov, Ftfc.Algorithm algorithm, double alpha)	Conctructor.

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

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

Modifier and Type	Method	Description
ICovarianceMatrix	GicScores.getCovariances()	Specialized scoring method for a single parent.
ICovarianceMatrix	PoissonPriorScore.getCovariances()
ICovarianceMatrix	SemBicScore.getCovariances()
ICovarianceMatrix	ZsbScore.getCovariances()

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

Modifier and Type	Method	Description
static double	SemBicScore.getVarRy(int i, int[] parents, Matrix data, ICovarianceMatrix covariances, boolean calculateRowSubsets)

Constructors in edu.cmu.tetrad.search.score with parameters of type ICovarianceMatrix

Modifier	Constructor	Description
	EbicScore(ICovarianceMatrix covariances)	Constructs the score using a covariance matrix.
	GicScores(ICovarianceMatrix covariances)	Constructs the score using a covariance matrix.
	PoissonPriorScore(ICovarianceMatrix covariances)	Constructs the score using a covariance matrix.
	SemBicScore(ICovarianceMatrix covariances)	Constructs the score using a covariance matrix.
	ZsbScore(ICovarianceMatrix covMatrix)	Constructs the score using a covariance matrix.

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

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

Modifier and Type	Method	Description
ICovarianceMatrix	IndTestFisherZ.getCov()	Returns the correlation matrix being analyzed.
ICovarianceMatrix	IndTestFisherZConcatenateResiduals.getCov()	Returns teh covaraince matrix of the concatenated data.
ICovarianceMatrix	IndTestFisherZFisherPValue.getCov()	Returns the covariance matrix of the concatenated data.
ICovarianceMatrix	IndTestTrekSep.getCov()	Returns the covariance matrix.
ICovarianceMatrix	Kci.getCov()
ICovarianceMatrix	ScoreIndTest.getCov()	Returns the covariance matrix.

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

Modifier	Constructor	Description
	IndTestFisherZ(ICovarianceMatrix covMatrix, double alpha)	Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.
	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.

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

Methods in edu.cmu.tetrad.search.utils that return ICovarianceMatrix

Modifier and Type	Method	Description
ICovarianceMatrix	TetradTest.getCovMatrix()
ICovarianceMatrix	TetradTestContinuous.getCovMatrix()
ICovarianceMatrix	TetradTestDiscrete.getCovMatrix()
ICovarianceMatrix	TetradTestPopulation.getCovMatrix()

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

Modifier and Type	Method	Description
void	TetradTestContinuous.setCovMatrix(ICovarianceMatrix covMatrix)

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

Modifier	Constructor	Description
	DeltaSextadTest(ICovarianceMatrix cov)	Constructs a test using the given covariance matrix.
	DeltaTetradTest(ICovarianceMatrix cov)	Constructs a test using the given covariance matrix.
	PartialCorrelation(ICovarianceMatrix cov)	Constructor
	TetradTestContinuous(ICovarianceMatrix covMatrix, BpcTestType sigTestType, double sig)

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

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

Modifier and Type	Method	Description
ICovarianceMatrix	IndTestFisherZPercentIndependent.getCov()
ICovarianceMatrix	IndTestFisherZRecursive.getCov()
ICovarianceMatrix	IndTestPositiveCorr.getCov()
ICovarianceMatrix	SampleVcpc.getCov()
ICovarianceMatrix	SampleVcpcFast.getCov()
ICovarianceMatrix	SemBicScoreDeterministic.getCovariances()

Constructors in edu.cmu.tetrad.search.work_in_progress with parameters of type ICovarianceMatrix

Modifier	Constructor	Description
	BpcTetradPurifyWashdown(ICovarianceMatrix cov, BpcTestType testType, double alpha)	Construct the algorithm using a covariance matrix.
	IndTestCramerT(ICovarianceMatrix covMatrix, double alpha)	Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.
	IndTestFisherZRecursive(ICovarianceMatrix covMatrix, double alpha)	Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.
	MagSemBicScore(ICovarianceMatrix covariances)	Constructor.
	SemBicScoreDeterministic(ICovarianceMatrix covariances)	Constructs the score using a covariance matrix.
	Washdown(ICovarianceMatrix cov, double alpha)	Constructor.

Uses of ICovarianceMatrix in edu.cmu.tetrad.sem

Methods in edu.cmu.tetrad.sem that return ICovarianceMatrix

Modifier and Type	Method	Description
ICovarianceMatrix	DagScorer.getCovMatrix()
ICovarianceMatrix	Scorer.getCovMatrix()
ICovarianceMatrix	SemEstimator.getCovMatrix()

Methods in edu.cmu.tetrad.sem with parameters of type ICovarianceMatrix

Modifier and Type	Method	Description
Ricf.RicfResult	Ricf.ricf(SemGraph mag, ICovarianceMatrix covMatrix, double tolerance)
Ricf.RicfResult	Ricf.ricf2(Graph mag, ICovarianceMatrix covMatrix, double tolerance)	same as above but takes a Graph instead of a SemGraph
void	SemIm.setCovMatrix(ICovarianceMatrix covMatrix)	Sets the sample covariance matrix for this Sem as a submatrix of the given matrix.

Constructors in edu.cmu.tetrad.sem with parameters of type ICovarianceMatrix

Modifier	Constructor	Description
	DagScorer(ICovarianceMatrix covMatrix)	Constructs a new SemEstimator that uses the specified optimizer.
	RicfResult(cern.colt.matrix.DoubleMatrix2D shat, cern.colt.matrix.DoubleMatrix2D lhat, cern.colt.matrix.DoubleMatrix2D bhat, cern.colt.matrix.DoubleMatrix2D ohat, int iterations, double diff, ICovarianceMatrix covMatrix)
	SemEstimator(ICovarianceMatrix covMatrix, SemPm semPm)	Constructs a SEM estimator that does default estimation.
	SemEstimator(ICovarianceMatrix covMatrix, SemPm semPm, SemOptimizer semOptimizer)	Constructs a new SemEstimator that uses the specified optimizer.
	SemIm(SemPm semPm, ICovarianceMatrix covMatrix)	Constructs a SEM model using the given SEM PM and sample covariance matrix.