Class IdaCheckAvgMinSquaredDiffEstTrue

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

public class IdaCheckAvgMinSquaredDiffEstTrue extends Object implements Statistic
Represents a statistic that calculates the average minimum squared difference between the estimated and true values for a given data model and graphs.
See Also:
  • Constructor Details

    • IdaCheckAvgMinSquaredDiffEstTrue

      public IdaCheckAvgMinSquaredDiffEstTrue()
      Calculates the average minimum squared difference between the estimated and true values for a given data model and graphs.
  • Method Details

    • getAbbreviation

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

      public double getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)
      Calculates the average minimum squared difference between the estimated and true values for a given data model and graphs.
      Specified by:
      getValue in interface Statistic
      Parameters:
      trueGraph - The true graph (DAG, CPDAG, PAG_of_the_true_DAG).
      estGraph - The estimated graph (same type).
      dataModel - The data model.
      Returns:
      The average minimum squared difference between the estimated and true values.
      Throws:
      IllegalArgumentException - if the data model is null.
    • getNormValue

      public double getNormValue(double value)
      Calculates the normalized value of a statistic.
      Specified by:
      getNormValue in interface Statistic
      Parameters:
      value - The value of the statistic.
      Returns:
      The normalized value of the statistic.