Uses of Interface
edu.cmu.tetrad.util.EffectiveSampleSizeSettable

Packages that use EffectiveSampleSizeSettable

Package	Description
edu.cmu.tetrad.search	This package contains classes for causal graph search algorithms.
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.

Uses of EffectiveSampleSizeSettable in edu.cmu.tetrad.search

Classes in edu.cmu.tetrad.search that implement EffectiveSampleSizeSettable

Modifier and Type	Class	Description
class	MarkovCheck	Checks whether a graph is Markov given a data set.
class	Tsc	Trek Separation Clusters (TSC): a rank-based algorithm for recovering the latent-cluster structure of a pure measurement model from an observed correlation or covariance matrix.

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

Classes in edu.cmu.tetrad.search.score that implement EffectiveSampleSizeSettable

Modifier and Type	Class	Description
class	BlocksBicScore	BlocksBicScoreTrekSoft
class	BlocksTrekBicScore	BlocksTrekBicScore: A trek-aware blocks-based BIC-style local score that mirrors the split construction used in block trek-separation tests.
class	ConditionalGaussianScore	Implements a conditional Gaussian BIC score for FGS, which calculates a BIC score for mixed discrete/Gaussian data using the conditional Gaussian likelihood function.
class	DegenerateGaussianScore	=This implements the degenerate Gaussian BIC score for FGES.
class	EbicScore	Implements the extended BIC (EBIC) score.
final class	FfCordContinuous	FF-DML: Feature-Function Distributional Marginal Likelihood score (GP form, continuous)
final class	FfDmlContinuous	FF-DML: Feature-Function Distributional Marginal Likelihood score (GP form, continuous)
final class	FfMl	FFML: Feature-Function Marginal Likelihood score for mixed (continuous + discrete) parents
final class	FfMlContinuous	FF-ML: Feature-Function Marginal Likelihood score (GP form, continuous)
class	GicScores	Implements scores motivated by the Generalized Information Criterion (GIC) approach as given in Kim et al.
final class	HeavyTailSemBicScore	A BIC-style local score for structural equation models (SEMs) that replaces the standard Gaussian log-likelihood with a heavier-tailed or more robust noise model, making it better suited to data with outliers or non-Gaussian residuals.
final class	HuangMarginalLikelihoodScore	Kernel-based marginal likelihood score of Huang et al.
final class	KcvBicScore	KCI-inspired local score for continuous variables.
final class	KernelMarginalLikelihoodScore	KML: Kernel Marginal Likelihood score for mixed (continuous + discrete) parents
final class	KernelMarginalLikelihoodScoreContinuous	Kernel Marginal Likelihood (KML) score for continuous variables.
final class	LegendreBicScore	Legendre BIC score
class	PoissonPriorScore	Implements Poisson prior score, a novel (unpubished) score that replaces the penalty term in BIC by the log of the Poisson distribution.
final class	RffBicScore	RCIT-inspired local score for continuous variables.
class	SemBicScore	Implements the linear, Gaussian BIC score, with a 'penalty discount' multiplier on the BIC penalty.
final class	TRffBicScore	TRFF BIC score (mixed)
class	ZsbScore	Implements an unpublished score based on a risk bound due to Zhang and Shen.

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

Classes in edu.cmu.tetrad.search.test that implement EffectiveSampleSizeSettable

Modifier and Type	Class	Description
class	IndTestBasisFunctionBlocks	Basis–function independence test using block–structured Wilks statistics.
class	IndTestBasisFunctionLrtFullSample	Deprecated.
class	IndTestBlocksLemma10	Deprecated.
class	IndTestBlocksWilkes	Block-level CI test using Wilks-rank.
final class	IndTestChiSquare	Checks the conditional independence X _||_ Y | S, where S is a set of discrete variable, and X and Y are discrete variable not in S, by applying a conditional Chi Square test.
class	IndTestConditionalGaussianLrt	Performs a test of conditional independence X _||_ Y | Z1...Zn where all variables are either continuous or discrete.
class	IndTestDegenerateGaussianLrt	Implements degenerate Gaussian test as a likelihood ratio test.
class	IndTestDegenerateGaussianLrtFullSample	Deprecated.
final class	IndTestFisherZ	Fisher's Z CI test with shrinkage (RIDGE/Ledoit-Wolf) and optional pseudoinverse fallback.
final class	IndTestGSquare	Checks the conditional independence X _||_ Y | S, where S is a set of discrete variable, and X and Y are discrete variable not in S, by applying a conditional G Square test.
class	TrekSeparationBlocksIndependence	A block-level conditional independence test based on trek separation, operating under linear latent factor measurement models.