Uses of Class
edu.cmu.tetrad.search.WildBootstrapMarkovCheck.Result

Packages that use WildBootstrapMarkovCheck.Result

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

Uses of WildBootstrapMarkovCheck.Result in edu.cmu.tetrad.search

Methods in edu.cmu.tetrad.search that return WildBootstrapMarkovCheck.Result

Modifier and Type	Method	Description
WildBootstrapMarkovCheck.Result	WildBootstrapMarkovCheck.checkFacts(List<IndependenceFact> facts)	Run the joint wild-bootstrap check against an explicit list of independence facts.
WildBootstrapMarkovCheck.Result	WildBootstrapMarkovCheck.checkMarkovBlanket(Graph graph)	Build the stacked product matrix from the data and graph, then run the joint check.
static WildBootstrapMarkovCheck.Result	WildBootstrapMarkovCheck.runEngine(double[][] product, String[] labels, int numBootstraps, long seed, WildBootstrapMarkovCheck.Multiplier mult)	Run the joint check directly on a precomputed product matrix.
static WildBootstrapMarkovCheck.Result	WildBootstrapMarkovCheck.runEngineBlocks(double[][] product, String[] labels, int numBootstraps, long seed, WildBootstrapMarkovCheck.Multiplier mult, int[] blocks)	Wild CLUSTER bootstrap-t engine for row dependence with a block (cluster) structure.
static WildBootstrapMarkovCheck.Result	WildBootstrapMarkovCheck.runEngineKernel(double[][] product, String[] labels, int numBootstraps, long seed, double[][] coords, double bandwidth)	Dependent wild bootstrap-t engine (Shao 2010, self-normalized) for row dependence indexed by coordinates (spatial locations; a single column of time indices for serial data).