Package edu.cmu.tetrad.search.score

Class EbicScore

java.lang.Object
edu.cmu.tetrad.search.score.EbicScore
All Implemented Interfaces:
Score
public class EbicScore extends Object implements Score
Implements the extended BIC (EBIC) score. The reference is here:

Chen, J., & Chen, Z. (2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika, 95(3), 759-771.

As for all scores in Tetrad, higher scores mean more dependence, and negative scores indicate independence.

Version:
$Id: $Id
Author:
josephramsey

  • Constructor Details

    • EbicScore

      public EbicScore(ICovarianceMatrix covariances)
      Constructs the score using a covariance matrix.
      Parameters:
      covariances - The covariance matrix.

    • EbicScore

      public EbicScore(DataSet dataSet, boolean precomputeCovariances)
      Constructs the score using a covariance matrix.
      Parameters:
      dataSet - The continuous dataset to analyze.
      precomputeCovariances - Whether the covariances should be precomputed or computed on the fly. True if precomputed.

  • Method Details

    • localScoreDiff

      public double localScoreDiff(int x, int y, int[] z)
      Returns the score difference of the graph.

      Returns the score of the node at index y, given its parents.

      Specified by:
      localScoreDiff in interface Score
      Parameters:
      x - A node.
      y - TAhe node.
      z - A set of nodes.
      Returns:
      The score difference.

    • localScore

      public double localScore(int i, int... parents) throws RuntimeException
      Returns the score of the node at index i, given its parents.
      Specified by:
      localScore in interface Score
      Parameters:
      i - The index of the node.
      parents - The indices of the node's parents.
      Returns:
      The score, or NaN if the score cannot be calculated.
      Throws:
      RuntimeException - if any.

    • getSampleSize

      public int getSampleSize()
      Returns the sample size.
      Specified by:
      getSampleSize in interface Score
      Returns:
      This size.

    • isEffectEdge

      public boolean isEffectEdge(double bump)
      Returns true iff the edge between x and y is an effect edge.

      Returns a judgement for FGES of whether the given bump implies an effect edge.

      Specified by:
      isEffectEdge in interface Score
      Parameters:
      bump - The bump.
      Returns:
      True iff the edge between x and y is an effect edge.
      See Also:

    • getVariables

      public List<Node> getVariables()
      The variables of the score.

      Returns the variables for this score.

      Specified by:
      getVariables in interface Score
      Returns:
      This list.

    • getMaxDegree

      public int getMaxDegree()
      Returns the max degree, by default 1000.

      Returns an estimate of max degree of the graph for some algorithms.

      Specified by:
      getMaxDegree in interface Score
      Returns:
      The max degree.
      See Also:

    • determines

      public boolean determines(List<Node> z, Node y)
      Returns true iff the score determines the edge between x and y.

      Return a judgment of whether the variable in z determine y exactly.

      Specified by:
      determines in interface Score
      Parameters:
      z - The set of nodes.
      y - The node.
      Returns:
      True iff the score determines the edge between x and y.

    • setGamma

      public void setGamma(double gamma)
      Sets the gamma parameter for EBIC.
      Parameters:
      gamma - The gamma parameter.

    • setUsePseudoInverse

      public void setUsePseudoInverse(boolean usePseudoInverse)
      Returns the gamma parameter for EBIC.
      Parameters:
      usePseudoInverse - True if the pseudo-inverse should be used.