Package edu.cmu.tetrad.search.test
package edu.cmu.tetrad.search.test
Contains classes for running conditional independence tests for various sorts of data.
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ClassDescriptionCalculates 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.The IndTestBasisFunctionLrtCovariance class implements the IndependenceTest interface and provides functionality to perform conditional independence tests using basis functions and likelihood ratio tests based on residual variances and covariance matrices.The IndTestBasisFunctionLrt class performs conditional independence testing using basis functions within the context of a generalized likelihood ratio test (GLRT).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.The IndTestBasisFunctionLrt class performs conditional independence testing using basis functions within the context of a generalized likelihood ratio test (GLRT).Checks conditional independence of variable in a continuous data set using Fisher's Z test.Calculates independence from pooled residuals using the Fisher Z method.Calculates independence from multiple datasets from using the Fisher method of pooling independence results.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.Checks the conditional independence X _||_ Y | S, where S is a set of continuous variable, and X and Y are discrete variable not in S, using the Hilbert-Schmidth Independence Criterion (HSIC), a kernel based nonparametric test for conditional independence.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.Checks independence of X _||_ Y | Z for variables X and Y and list Z of variables by regressing X on {Y} U Z and testing whether the coefficient for Y is zero.Checks d-separations in a structural model using t-separations over indicators.Gives an implementation of the Kernel Independence Test (KCI) by Kun Zhang, which is a general test of conditional independence.A record representing the result of an eigenvalue decomposition.Represents the type of kernel to be used in a computation.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.The class is used to find the top eigenvalues and eigenvectors of a given matrix.