Package edu.cmu.tetrad.algcomparison.statistic

Class MathewsCorrArrow

java.lang.Object
edu.cmu.tetrad.algcomparison.statistic.MathewsCorrArrow
All Implemented Interfaces:
Statistic, Serializable
public class MathewsCorrArrow extends Object implements Statistic
Calculates the Matthew's correlation coefficient for adjacencies. See this page in Wikipedia: https://en.wikipedia.org/wiki/Matthews_correlation_coefficient We calculate the correlation directly from the confusion matrix. if the true contains X*->Y and estimated graph either does not contain an edge from X to Y or else does not contain an arrowhead at X for an edge from X to Y, one false positive is counted. Similarly, for false negatives
Author:
jdramsey
See Also:

  • Constructor Details

    • MathewsCorrArrow

      public MathewsCorrArrow()

  • Method Details

    • getAbbreviation

      public String getAbbreviation()
      Description copied from interface: Statistic
      The abbreviation for the statistic. This will be printed at the top of each column.
      Specified by:
      getAbbreviation in interface Statistic
      Returns:
      Thsi abbreviation.

    • getDescription

      public String getDescription()
      Description copied from interface: Statistic
      Returns a short one-line description of this statistic. This will be printed at the beginning of the report.
      Specified by:
      getDescription in interface Statistic
      Returns:
      This description.

    • getValue

      public double getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)
      Description copied from interface: Statistic
      Returns the value of this statistic, given the true graph and the estimated graph.
      Specified by:
      getValue in interface Statistic
      Parameters:
      trueGraph - The true graph (DAG, CPDAG, PAG_of_the_true_DAG).
      estGraph - The estimated graph (same type).
      Returns:
      The value of the statistic.

    • getNormValue

      public double getNormValue(double value)
      Description copied from interface: Statistic
      Returns a mapping of the statistic to the interval [0, 1], with higher being better. This is used for a calculation of a utility for an algorithm.If the statistic is already between 0 and 1, you can just return the statistic.
      Specified by:
      getNormValue in interface Statistic
      Parameters:
      value - The value of the statistic.
      Returns:
      The weight of the statistic, 0 to 1, higher is better.