Class DefiniteDirectedPathPrecision

java.lang.Object
edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathPrecision
All Implemented Interfaces:
Statistic, Serializable

public class DefiniteDirectedPathPrecision extends Object implements Statistic
The bidirected true positives.
Version:
$Id: $Id
Author:
josephramsey
See Also:
  • Constructor Details

    • DefiniteDirectedPathPrecision

      public DefiniteDirectedPathPrecision()
      Initializes a new instance of the DefiniteDirectedPathPrecision class.
  • Method Details

    • getAbbreviation

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

      public String getDescription()
      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 trueDag, Graph trueGraph, Graph estGraph, DataModel dataModel, Parameters parameters)
      Calculates and returns the value of the statistic based on the provided graphs, data model, and parameters.
      Specified by:
      getValue in interface Statistic
      Parameters:
      trueDag - The true directed acyclic graph (DAG).
      trueGraph - The true graph, which could be a DAG, a CPDAG, or a PAG derived from the true DAG.
      estGraph - The estimated graph, which corresponds to the same type as the trueGraph.
      dataModel - The data model, which may be null.
      parameters - The parameters for the calculation, which may be null.
      Returns:
      The computed value of the statistic as a double.
    • getNormValue

      public double getNormValue(double value)
      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.