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

Packages that use ICovarianceMatrix

Package	Description
edu.cmu.tetrad.data
edu.cmu.tetrad.data.audit
edu.cmu.tetrad.data.missing
edu.cmu.tetrad.regression
edu.cmu.tetrad.search	This package contains classes for causal graph search algorithms.
edu.cmu.tetrad.search.is
edu.cmu.tetrad.search.rlcd
edu.cmu.tetrad.search.score	This package contains classes for scoring causal graph models.
edu.cmu.tetrad.search.test	This package contains classes for testing causal graph search algorithms.
edu.cmu.tetrad.search.utils	This package contains utility classes for causal graph search algorithms.
edu.cmu.tetrad.search.work_in_progress	A package for algorithms that are not 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.covarianceGaussianCopula(DataSet dataSet)	Returns the Gaussian copula ("nonparanormal") correlation matrix of a continuous data set: for each pair of variables the sample Kendall's tau-b is computed and mapped to the latent Gaussian correlation by
static ICovarianceMatrix	DataTransforms.covarianceNonparanormalDrton(DataSet dataSet)	Deprecated. This does NOT compute the nonparanormal (Gaussian copula) correlation estimator, despite the name.
ICovarianceMatrix	EmCovarianceEstimator.estimate()	Runs EM and returns the estimated covariance matrix.
static ICovarianceMatrix	EmCovarianceEstimator.estimateCovariance(DataSet dataSet)	Convenience method: estimates and returns the covariance matrix for the given dataset using default settings.
static @NotNull ICovarianceMatrix	SimpleDataLoader.getCorrelationMatrix(DataSet dataSet)	getCorrelationMatrix.
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)	getCovarianceMatrix.
final ICovarianceMatrix	CorrelationMatrixOnTheFly.getSubmatrix(int[] indices)	getSubmatrix.
final ICovarianceMatrix	CorrelationMatrixOnTheFly.getSubmatrix(List<String> submatrixVarNames)	getSubmatrix.
final ICovarianceMatrix	CovarianceMatrix.getSubmatrix(int[] indices)	getSubmatrix.
final ICovarianceMatrix	CovarianceMatrix.getSubmatrix(List<String> submatrixVarNames)	getSubmatrix.
final ICovarianceMatrix	CovarianceMatrixOnTheFly.getSubmatrix(int[] indices)	getSubmatrix.
final ICovarianceMatrix	CovarianceMatrixOnTheFly.getSubmatrix(int[] indices, int[] dataRows)	getSubmatrix.
final ICovarianceMatrix	CovarianceMatrixOnTheFly.getSubmatrix(List<String> submatrixVarNames)	getSubmatrix.
ICovarianceMatrix	ICovarianceMatrix.getSubmatrix(int[] indices)	Returns a submatrix of the covariance matrix, including only the specified variables.
ICovarianceMatrix	ICovarianceMatrix.getSubmatrix(String[] submatrixVarNames)	Returns a submatrix of the covariance matrix, including only the specified variables.
ICovarianceMatrix	ICovarianceMatrix.getSubmatrix(List<String> submatrixVarNames)	Returns a submatrix of the covariance matrix, including only the specified variables.
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)	getExampleNonsingular.
static Matrix	DataUtils.subMatrix(ICovarianceMatrix m, Node x, Node y, List<Node> z)	subMatrix.
static Matrix	DataUtils.subMatrix(ICovarianceMatrix m, Map<Node,Integer> indexMap, Node x, Node y, List<Node> z)	subMatrix.
static void	DataWriter.writeCovMatrixLowerTriangle(ICovarianceMatrix covMatrix, PrintWriter out, NumberFormat nf)	Writes the lower triangle of a covariance matrix to file.
static void	DataWriter.writeCovMatrixSquare(ICovarianceMatrix covMatrix, PrintWriter out, NumberFormat nf)	Writes the covariance matrix to file as a square matrix.

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)	Constructor for CovarianceMatrix.

Uses of ICovarianceMatrix in edu.cmu.tetrad.data.audit

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

Modifier	Constructor	Description
	CovarianceAudit(ICovarianceMatrix cov)	Audits the given covariance matrix with default thresholds.
	CovarianceAudit(ICovarianceMatrix cov, CovarianceAudit.Config config)	Audits the given covariance matrix with the given thresholds.

Uses of ICovarianceMatrix in edu.cmu.tetrad.data.missing

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

Modifier and Type	Method	Description
ICovarianceMatrix	CensoredMvnCovarianceEstimator.estimate()	The estimated covariance matrix, computed on first call.
static ICovarianceMatrix	PairwiseCovarianceEstimator.estimate(DataSet data)	Estimates the covariance matrix of the dataset's columns.
static ICovarianceMatrix	MissingDataUtils.estimateCovariance(DataSet dataSet, MissingDataSpec spec)	The covariance matrix of a dataset with missing values under a policy that estimates one: by EM with the spec's ridge, tolerance and iteration limit under EM_COVARIANCE, or by pairwise deletion (PairwiseCovarianceEstimator) under PAIRWISE_COVARIANCE.
ICovarianceMatrix	TestwiseCovariance.pairwiseCovarianceMatrix(List<Node> variables)	Returns a pairwise-deletion covariance matrix over the given variables: entry (i, j) is the covariance of columns i and j over the rows complete on both, with each diagonal entry computed over the rows complete on that column alone.

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
ICovarianceMatrix	MimbuildTrek.getLatentsCov()	Deprecated. The covariance matrix over the latents that is implied by the clustering.
ICovarianceMatrix	MimbuildBollen.getLatentsCovariance()	Retrieves the latent covariance matrix associated with the MimbuildBollen instance.
ICovarianceMatrix	MimbuildPca.getLatentsCovariance()	Retrieves the latent covariance matrix, which encapsulates the covariances between the latent variables associated with the specified blocks in the PCA analysis.

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

Modifier and Type	Method	Description
Graph	MimbuildTrek.search(List<List<Node>> clustering, List<String> latentNames, ICovarianceMatrix measuresCov)	Deprecated. Does the search and returns the graph.
void	BfciScoreCheck.setCovarianceMatrix(ICovarianceMatrix covarianceMatrix)	Sets the covariance matrix used by the RICF score check.
void	FcitSlScoreCheck.setCovarianceMatrix(ICovarianceMatrix covarianceMatrix)	Sets the covariance matrix used by the MAG score check explicitly.
void	Gmas.setCovarianceMatrix(ICovarianceMatrix covarianceMatrix)	Sets the covariance matrix used by the MAG score explicitly.

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

Modifier	Constructor	Description
	FactorAnalysis(ICovarianceMatrix covarianceMatrix)	Constructor.
	Flop(ICovarianceMatrix covariances)	Constructs a FLOP search over the given covariance matrix.
	GRegression(Graph mpdag, ICovarianceMatrix cov)	Constructs a G-regression estimator for the given MPDAG and covariance matrix.
	GRegressionPag(Graph pag, ICovarianceMatrix cov)	Constructs the estimator with default RICF settings.
	GRegressionPag(Graph pag, ICovarianceMatrix cov, double tol, int maxIters)	Constructs the estimator, fitting the Gaussian ancestral graph model once.

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

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

Modifier and Type	Method	Description
ICovarianceMatrix	IndTestProbabilisticBDeu.getCov()	Retrieves the covariance matrix associated with this independence test.
ICovarianceMatrix	IndTestProbabilisticISBDeu.getCov()	Retrieves the covariance matrix used in the computation.
ICovarianceMatrix	IsGFci.getCovarianceMatrix()	Returns the covariance matrix associated with this instance.

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

Modifier and Type	Method	Description
void	IsGFci.setCovarianceMatrix(ICovarianceMatrix covarianceMatrix)	Sets the covariance matrix for the instance.

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

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

Modifier	Constructor	Description
	Chi2RankTest(ICovarianceMatrix cov, double nScaling)	Constructs the test from a covariance or correlation matrix.
	EmCovarianceRankTest(ICovarianceMatrix cov, int[][] pairwiseCounts, int numRows)	Constructs the test over an estimated covariance matrix with the mean-pairwise sample-size rule.
	EmCovarianceRankTest(ICovarianceMatrix cov, int[][] pairwiseCounts, int numRows, MissingDataSpec.EffectiveSampleSizeMode essMode, double nScaling)	Constructs the test over an estimated covariance matrix.

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	BgeScore.getCovariances()	Returns the covariance matrix the score is computed from, or null under test-wise deletion (where there is no single covariance matrix; each family has its own).
ICovarianceMatrix	GicScores.getCovariances()	Returns the sample size.
ICovarianceMatrix	PoissonPriorScore.getCovariances()	Returns the covariance matrix.
ICovarianceMatrix	SemBicScore.getCovariances()	Returns the covariance matrix.
ICovarianceMatrix	ZsbScore.getCovariances()	Returns the covariance matrix.

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

Modifier and Type	Method	Description
static SemBicScore.CovAndCoefs	SemBicScore.getCovAndCoefs(int i, int[] parents, Matrix data, ICovarianceMatrix covariances, boolean calculateRowSubsets, double lambda)	Returns the covariance matrix of the regression of the ith variable on its parents and the regression coefficients.
static @NotNull SemBicScore.CovAndCoefs	SemBicScore.getCovAndCoefs(int i, int[] parents, Matrix data, ICovarianceMatrix covariances, double lambda, List<Integer> rows)	Returns the covariance matrix of the regression of the ith variable on its parents and the regression
static double	SemBicScore.getResidualVariance(int i, int[] parents, Matrix data, ICovarianceMatrix covariances, boolean calculateRowSubsets, double lambda)	Returns the variance of the residual of the regression of the ith variable on its parents.

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

Modifier	Constructor	Description
	BgeScore(ICovarianceMatrix covariances)	Constructs a BGe score from a covariance matrix.
	EbicScore(ICovarianceMatrix covariances)	Constructs the score using a covariance matrix.
	GicScores(ICovarianceMatrix covariances)	Constructs the score using a covariance matrix.
	InstanceAugmentedSemBicScore(ICovarianceMatrix cov, double[] instanceRowCentered)	Constructs an `InstanceAugmentedSemBicScore` object using a covariance matrix and a fully centered row of instance data.
	InstanceAugmentedSemBicScore(ICovarianceMatrix cov, double[] instanceRowRaw, double[] populationMeans)	Constructs an `InstanceAugmentedSemBicScore` object using a covariance matrix, a raw row of instance data, and the population mean values.
	MagRicfBicScorer(ICovarianceMatrix cov)	Constructs the scorer for a covariance matrix.
	PoissonPriorScore(ICovarianceMatrix covariances)	Constructs the score using a covariance matrix.
	SemBicScore(ICovarianceMatrix covariances)	Constructs the score using a covariance matrix.
	SemBicScore(ICovarianceMatrix covariances, double penaltyDiscount)	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	CachingIndependenceTest.getCov()	Returns the covariance matrix of the base test.
ICovarianceMatrix	EdgePriorTest.getCov()	Returns the covariance matrix of the wrapped test.
default ICovarianceMatrix	IndependenceTest.getCov()	Returns the covariance matrix.
ICovarianceMatrix	IndTestFisherZ.getCov()	Retrieves the covariance matrix used by this instance.
ICovarianceMatrix	IndTestFisherZConcatenateResiduals.getCov()	Deprecated. Returns the covariance matrix for the data sets.
ICovarianceMatrix	IndTestFisherZFisherPValue.getCov()	Returns the covariance matrix of the concatenated data.
ICovarianceMatrix	IndTestTrekSep.getCov()	Deprecated. Returns the covariance matrix.
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 an instance of IndTestFisherZ using the given covariance matrix and significance level.
	IndTestFisherZ(ICovarianceMatrix covMatrix, double alpha, double ridge)	Constructor for the IndTestFisherZ class.
	IndTestTrekSep(ICovarianceMatrix covMatrix, double alpha, List<List<Node>> clustering, List<Node> latents)	Deprecated. 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()	getCovMatrix.
ICovarianceMatrix	TetradTestContinuous.getCovMatrix()	getCovMatrix.
ICovarianceMatrix	TetradTestDiscrete.getCovMatrix()	getCovMatrix.
ICovarianceMatrix	TetradTestPopulation.getCovMatrix()	getCovMatrix.

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

Modifier and Type	Method	Description
static List<Node>	FlopInitialOrder.initialOrder(ICovarianceMatrix covariances)	Computes the FLOP initial order for the variables of the given covariance matrix.
static Map<Integer, List<Integer>>	Embedding.pruneUninformativeBasisColumns(DataSet dataSet, Map<Integer, List<Integer>> embedding, ICovarianceMatrix embeddedCorr)	Prunes uninformative basis columns from an embedding using a BIC-crossing screen, so that the effective truncation of each continuous variable is chosen by the data rather than by the truncationLimit parameter.
void	TetradTestContinuous.setCovMatrix(ICovarianceMatrix covMatrix)	Setter for the field 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 covarianceMatrix)	Constructor for a covariance matrix.
	DeltaTetradTest2(ICovarianceMatrix cov)	Constructs a test using the given covariance matrix.
	DeltaTetradTest3(ICovarianceMatrix covarianceMatrix)	Constructor for a covariance matrix.
	PartialCorrelation(ICovarianceMatrix cov)	Constructor

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()	Deprecated. Retrieves the covariance matrix.
ICovarianceMatrix	IndTestFisherZRecursive.getCov()	Deprecated. getCov.
ICovarianceMatrix	IndTestPositiveCorr.getCov()	Deprecated. getCov.
ICovarianceMatrix	SampleVcpc.getCov()	getCov.
ICovarianceMatrix	SampleVcpcFast.getCov()	getCov.
ICovarianceMatrix	SemBicScoreDeterministic.getCovariances()	Getter for the field covariances.

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

Modifier	Constructor	Description
	IndTestCramerT(ICovarianceMatrix covMatrix, double alpha)	Deprecated. 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)	Deprecated. 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()	Getter for the field covMatrix.
ICovarianceMatrix	Scorer.getCovMatrix()	getCovMatrix.
ICovarianceMatrix	SemEstimator.getCovMatrix()	Getter for the field covMatrix.

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

Modifier and Type	Method	Description
static double	Ricf.logLikMAG(cern.colt.matrix.DoubleMatrix2D B, cern.colt.matrix.DoubleMatrix2D Omega, cern.colt.matrix.DoubleMatrix2D Lambda, int[] ug, ICovarianceMatrix covMatrix)	Calculates the log-likelihood for a Mixed Ancestral Graph (MAG) model given the input matrices and provides a measure of model fit.
Ricf.RicfResult	Ricf.ricf(SemGraph mag, ICovarianceMatrix covMatrix, double tolerance)	Calculates the Restricted Information Criterion Fusion (RICF) for a given SemGraph.
RicfEjml.RicfResult	RicfEjml.ricf(Graph admg, ICovarianceMatrix covMatrix)	Runs RICF with the default tolerance and iteration cap.
RicfEjml.RicfResult	RicfEjml.ricf(Graph admg, ICovarianceMatrix covMatrix, double tol, int maxIters)	Runs Residual Iterative Conditional Fitting for a Gaussian ADMG/MAG.
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)	The result.
	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.