Class IndTestBasisFunctionLrt

java.lang.Object
edu.cmu.tetrad.search.test.IndTestBasisFunctionLrt
All Implemented Interfaces:
RawMarginalIndependenceTest, IndependenceTest, RowsSettable
@Deprecated public class IndTestBasisFunctionLrt extends Object implements IndependenceTest, RawMarginalIndependenceTest, RowsSettable
Deprecated.
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

  • Constructor Details

    • IndTestBasisFunctionLrt

      public IndTestBasisFunctionLrt(DataSet dataSet, int truncationLimit, double lambda)
      Deprecated.
      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

    • IndTestBasisFunctionLrt

      public IndTestBasisFunctionLrt(DataSet dataSet, int truncationLimit, double lambda, MissingDataSpec spec)
      Deprecated.
      Constructs the test with an explicit missing-data specification. On a data set with missing values the supported policies are LISTWISE and TESTWISE. Under TESTWISE the embedding carries NaN in every derived column of a variable wherever that variable is missing, and each test computes the covariance of the embedded columns of x, y, and z over the rows complete on all of them, using the number of such rows as the sample size of the likelihood ratio statistic. A null spec on missing data is treated as FAIL.
      Parameters:
      dataSet - The data being analyzed.
      truncationLimit - The truncation limit of the basis.
      lambda - The singularity lambda.
      spec - The missing-data specification, or null.

  • Method Details

    • computePValue

      public double computePValue(double[] x, double[] y)
      Deprecated.
      Description copied from interface: RawMarginalIndependenceTest
      Computes the p-value for the statistical test of marginal independence between the two given variables represented by the input arrays.
      Specified by:
      computePValue in interface RawMarginalIndependenceTest
      Parameters:
      x - the first variable, represented as an array of doubles
      y - the second variable, represented as an array of doubles
      Returns:
      the computed p-value for the test of marginal independence

    • checkIndependence

      public IndependenceResult checkIndependence(Node x, Node y, Set<Node> z)
      Deprecated.
      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()
      Deprecated.
      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()
      Deprecated.
      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()
      Deprecated.
      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)
      Deprecated.
      Enables or disables verbose output.
      Specified by:
      setVerbose in interface IndependenceTest
      Parameters:
      verbose - True, if so.

    • getAlpha

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

    • setDoOneEquationOnly

      public void setDoOneEquationOnly(boolean doOneEquationOnly)
      Deprecated.
      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.

    • getRows

      public List<Integer> getRows()
      Deprecated.
      Description copied from interface: RowsSettable
      Gets the rows to use for the test. These rows over override testwise deletion if set.
      Specified by:
      getRows in interface RowsSettable
      Returns:
      The rows to use for the test. Can be null.

    • setRows

      public void setRows(List<Integer> rows)
      Deprecated.
      Description copied from interface: RowsSettable
      Sets the rows to use for the test. This will override testwise deletion.
      Specified by:
      setRows in interface RowsSettable
      Parameters:
      rows - The rows to use for the test. Can be null.

    • getMissingValueSupport

      public MissingValueSupport getMissingValueSupport()
      Deprecated.
      Declares what this test can do, natively, with data containing missing values. The default is MissingValueSupport.NONE, meaning that missingness must be handled upstream (e.g., by imputation, or by supplying an EM-estimated covariance matrix if the test consumes one); tests that handle missing values themselves should override this.

      TESTWISE: constructed with MissingDataSpec.testwise(), each test uses the rows complete on the embedded columns of x, y, and z.

      Specified by:
      getMissingValueSupport in interface IndependenceTest
      Returns:
      This support level.