Package edu.cmu.tetrad.search.test
package edu.cmu.tetrad.search.test
This package contains classes for testing causal graph search algorithms.
-
ClassDescriptionTags an independence test that operates over blocks.A caching wrapper for IndependenceTest.Calculates chi-square or g-square for a conditional cross-tabulation table for independence question 0 _||_ 1 | 2, 3, ...max by summing up chi-square and degrees of freedom for each conditional table in turn, where rows or columns that sum to less than a given threshold have been removed.The type of cell table to use.Simple class to store the parameters of the result returned by the G Square test.The type of test to perform.Checks conditional independence of variable in a continuous data set using Daudin's method.Stores a single conditional independence result, e.g., whether X _||_ Y | Z1,...,Zn holds or does not, and the p-value of the test.Gives an interface that can be implemented by classes that do conditional independence testing.IndTestBasisFunctionBlocks - Builds a per-variable truncated basis expansion (via Embedding) - Constructs the blocks mapping (original var -> list of embedded column indices) - Delegates CI testing to IndTestBlocks over those blocksDeprecated.Deprecated.Deprecated.Equality mode for the Lemma-10 criterion.Trek-separation block-level CI test (IndTestBlocksTs):Block-level CI test using Wilks-rank.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.Checks conditional independence of variable in a continuous data set using a conditional correlation test for the nonlinear nonGaussian with the additive error case.Performs a test of conditional independence X _||_ Y | Z1...Zn where all searchVariables are either continuous or discrete.Implements degenerate Gaussian test as a likelihood ratio test.Deprecated.Wrapper class for
IndependenceTestthat enforces False Discovery Rate (FDR) control on independence decisions.Fisher's Z CI test with shrinkage (RIDGE/LedoitâWolf) and optional pseudoinverse fallback.Shrinkage mode.Deprecated.Calculates independence from multiple datasets from using the Fisher method of pooling independence results.GIN (Generalized Independent Noise) conditional independence test.Distance correlation (biased) with optional permutations.Represents a ridge-regularized ordinary least squares (OLS) regressor.Fast Pearson correlation t-test (linear).How we compute residuals.Unconditional independence backend rX ⟂ rY → p-valueChecks 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.Deprecated.Checks conditional independence against a list of conditional independence facts, manually entered.A class that represents a pooled independence test for multiple data sets.Performs a test of conditional independence X _||_ Y | Z1...Zn where all variables are either continuous or discrete.Uses BCInference by Cooper and Bui to calculate probabilistic conditional independence judgments.RCIT (Randomized Conditional Independence Test) / RCoT (if doRcit=false).Deprecated.Deprecated.Use IndTestBlocksTs instead.The Kci class implements the Kernel-based Conditional Independence (KCI) test for statistical independence between variables.Enum representing the type of kernel function used in kernel-based computations.Checks independence facts for variables associated with the nodes in a given graph by checking m-separation facts on the underlying nodes.Interface for tests that can have their rows set on the fly.Gives a way of interpreting a score as an independence test.