Class IndTestFisherZGeneralizedInverse

java.lang.Object
edu.cmu.tetrad.search.work_in_progress.IndTestFisherZGeneralizedInverse
All Implemented Interfaces:
IndependenceTest

public final class IndTestFisherZGeneralizedInverse extends Object implements IndependenceTest
Checks independence of X _||_ Y | Z for variables X and Y and list Z of variables. Partial correlations are calculated using generalized inverses, so linearly dependent variables do not throw exceptions. Must supply a continuous data set; don't know how to do this with covariance or correlation matrices.
Author:
josephramsey, Frank Wimberly adapted IndTestCramerT for Fisher's Z
  • Constructor Details

    • IndTestFisherZGeneralizedInverse

      public IndTestFisherZGeneralizedInverse(DataSet dataSet, double alpha)
      Constructs a new Independence test which checks independence facts based on the correlation matrix implied by the given data set (must be continuous). The given significance level is used.
      Parameters:
      dataSet - A data set containing only continuous columns.
      alpha - The alpha level of the test.
  • Method Details

    • indTestSubset

      public IndependenceTest indTestSubset(List<Node> vars)
      Creates a new IndTestCramerT instance for a subset of the variables.
      Specified by:
      indTestSubset in interface IndependenceTest
      Parameters:
      vars - The sublist of variables.
    • checkIndependence

      public IndependenceResult checkIndependence(Node xVar, Node yVar, Set<Node> _z)
      Determines whether variable x is independent of variable y given a list of conditioning variables z.
      Specified by:
      checkIndependence in interface IndependenceTest
      Parameters:
      xVar - the one variable being compared.
      yVar - the second variable being compared.
      _z - the list of conditioning variables.
      Returns:
      True iff x _||_ y | z.
      Throws:
      RuntimeException - if a matrix singularity is encountered.
      See Also:
    • getPValue

      public double getPValue()
      Returns:
      the probability associated with the most recently computed independence test.
    • getAlpha

      public double getAlpha()
      Gets the getModel significance level.
      Specified by:
      getAlpha in interface IndependenceTest
      Returns:
      This level.
    • setAlpha

      public void setAlpha(double alpha)
      Sets the significance level at which independence judgments should be made. Affects the cutoff for partial correlations to be considered statistically equal to zero.
      Specified by:
      setAlpha in interface IndependenceTest
      Parameters:
      alpha - This level.
    • getVariables

      public List<Node> getVariables()
      Specified by:
      getVariables in interface IndependenceTest
      Returns:
      the list of variables over which this independence checker is capable of determinine independence relations-- that is, all the variables in the given graph or the given data set.
    • toString

      public String toString()
      Description copied from interface: IndependenceTest
      Returns a string representation of this test.
      Specified by:
      toString in interface IndependenceTest
      Overrides:
      toString in class Object
      Returns:
      the variable with the given name.
    • getData

      public DataSet getData()
      Returns the data being analyzed.
      Specified by:
      getData in interface IndependenceTest
      Returns:
      This data.
      See Also:
    • isVerbose

      public boolean isVerbose()
      Returns True just in case verbose output should be printed.
      Specified by:
      isVerbose in interface IndependenceTest
      Returns:
      This.
    • setVerbose

      public void setVerbose(boolean verbose)
      Sets whether verbose output should be printed.
      Specified by:
      setVerbose in interface IndependenceTest
      Parameters:
      verbose - True, if so.
    • determines

      public boolean determines(List<Node> zList, Node xVar)
      Returns true just in case the varialbe in zList determine xVar.
      Returns:
      True, if so.