Package edu.cmu.tetrad.search

Interface IndependenceTest

All Known Implementing Classes:
IndTestChiSquare, IndTestCodec, IndTestConditionalCorrelation, IndTestConditionalCorrelationLingam, IndTestConditionalGaussianLRT, IndTestCramerT, IndTestDegenerateGaussianLRT, IndTestDSep, IndTestFisherZ, IndTestFisherZConcatenateResiduals, IndTestFisherZFisherPValue, IndTestFisherZGeneralizedInverse, IndTestFisherZPercentIndependent, IndTestFisherZRecursive, IndTestGSquare, IndTestHsic, IndTestIndependenceFacts, IndTestMixedMultipleTTest, IndTestMNLRLRT, IndTestMulti, IndTestMultinomialLogisticRegression, IndTestMultinomialLogisticRegressionWald, IndTestMVPLRT, IndTestPositiveCorr, IndTestProbabilistic, IndTestRegression, IndTestScore, IndTestSepset, IndTestTrekSep, Kci, ProbabilisticMAPIndependence
public interface IndependenceTest
Interface implemented by classes that do conditional independence testing. These classes are capable of serving as conditional independence "oracles" for constraint-based searches.
Author:
Joseph Ramsey

  • Method Details

    • checkIndependence

      IndependenceResult checkIndependence(Node x, Node y, List<Node> z)
      Returns:
      an IndependenceResult (see).
      See Also:

    • getVariables

      List<Node> getVariables()
      Returns:
      the list of variables over which this independence checker is capable of determinining independence relations.

    • getData

      DataModel getData()
      Returns:
      The data model for the independence test.

    • getScore

      double getScore()
      A score that is higher with more likely models.

    • setVerbose

      void setVerbose(boolean verbose)

    • isVerbose

      boolean isVerbose()

    • toString

      String toString()
      Overrides:
      toString in class Object

    • indTestSubset

      default IndependenceTest indTestSubset(List<Node> vars)
      Returns:
      an Independence test for a subset of the variables.

    • checkIndependence

      default IndependenceResult checkIndependence(Node x, Node y, Node... z)
      Returns:
      and IndependenceResult (see).
      See Also:

    • getSampleSize

      default int getSampleSize()

    • getVariable

      default Node getVariable(String name)
      Returns:
      the variable by the given name.

    • getVariableNames

      default List<String> getVariableNames()
      Returns:
      the list of names for the variables in getNodesInEvidence.

    • determines

      default boolean determines(List<Node> z, Node y)
      Returns:
      true if y is determined the variable in z.

    • getAlpha

      default double getAlpha()
      Returns:
      the significance level of the independence test.
      Throws:
      UnsupportedOperationException - if there is no significance level.

    • setAlpha

      default void setAlpha(double alpha)
      Sets the significance level.

    • getCov

      default ICovarianceMatrix getCov()

    • getDataSets

      default List<DataSet> getDataSets()