Package edu.cmu.tetrad.search.test

Class IndTestBasisFunctionLrt

java.lang.Object
edu.cmu.tetrad.search.test.IndTestBasisFunctionLrt
All Implemented Interfaces:
IndependenceTest
public class IndTestBasisFunctionLrt extends Object implements IndependenceTest
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. It handles the transformations, embeddings, and statistical computations required to compute p-values for testing conditional independence of variables.

This class is designed to work with a given dataset, perform embedding transformations based on specified basis function parameters, and efficiently compute the required statistics for hypothesis testing over sets of variables.

Note that compared to the full sample version of this class (see), this class uses a covariance matrix as a sufficient statistic and thus cannot do random row subsetting per test.

Author:
josephramsey, bryanandrews
See Also:

  • Constructor Details

    • IndTestBasisFunctionLrt

      public IndTestBasisFunctionLrt(DataSet dataSet, int truncationLimit, double lambda)
      Constructs an instance of IndTestBasisFunctionLrtCovariance. This constructor initializes the object using a dataset and parameters related to truncation limit, basis type, and basis scale. It processes the input data into an embedded format, computes its covariance matrix, and sets up internal variables for further use.
      Parameters:
      dataSet - the input dataset containing the variables and data rows to be analyzed.
      truncationLimit - the limit to truncate the embeddings or basis functions in the data.
      lambda - Singularity lambda

  • Method Details

    • checkIndependence

      public IndependenceResult checkIndependence(Node x, Node y, Set<Node> z)
      Tests for the conditional independence of two nodes given a set of conditioning nodes.
      Specified by:
      checkIndependence in interface IndependenceTest
      Parameters:
      x - The first variable to test, represented as a Node object.
      y - The second variable to test, represented as a Node object.
      z - The set of conditioning variables, represented as a Set of Node objects.
      Returns:
      An IndependenceResult object representing the outcome of the independence test.

    • getVariables

      public List<Node> getVariables()
      Retrieves the list of nodes (variables) associated with this instance.
      Specified by:
      getVariables in interface IndependenceTest
      Returns:
      a list of Node objects representing the variables.

    • getData

      public DataModel getData()
      Retrieves the data model associated with this instance.
      Specified by:
      getData in interface IndependenceTest
      Returns:
      the current DataModel instance held by this class.

    • isVerbose

      public boolean isVerbose()
      Indicates whether verbose mode is enabled. Verbose mode, when enabled, typically results in detailed logging or diagnostic information being output.
      Specified by:
      isVerbose in interface IndependenceTest
      Returns:
      true if verbose mode is enabled; false otherwise.

    • setVerbose

      public void setVerbose(boolean verbose)
      Enables or disables verbose output.
      Specified by:
      setVerbose in interface IndependenceTest
      Parameters:
      verbose - True, if so.

    • getAlpha

      public double getAlpha()
      Retrieves the significance level (alpha) for the statistical tests performed by this instance.
      Specified by:
      getAlpha in interface IndependenceTest
      Returns:
      the current significance level as a double.

    • setAlpha

      public void setAlpha(double alpha)
      Sets the significance level.
      Specified by:
      setAlpha in interface IndependenceTest
      Parameters:
      alpha - This level.

    • setDoOneEquationOnly

      public void setDoOneEquationOnly(boolean doOneEquationOnly)
      When calculation the score for X = <X1 = X, X2, X3,..., Xp> use the equation for X1 only, if true; otherwise, use equations for all of X1, X2,...,Xp.
      Parameters:
      doOneEquationOnly - True if only the equation for X1 is to be used for X = X1,...,Xp.