Package edu.cmu.tetrad.search

Class ChiSquareTest

java.lang.Object
edu.cmu.tetrad.search.ChiSquareTest
Direct Known Subclasses:
GSquareTest
public class ChiSquareTest extends Object
Calculates marginal chi square test results for a discrete dataset.
Author:
Frank Wimberly original version, Joseph Ramsey revision 10/01, believe it or now also 2020.

  • Nested Class Summary

    Nested Classes
    Modifier and Type
    Class
    Description
    static class 
    ChiSquareTest.Result
    Simple class to store the parameters of the result returned by the G Square test.

  • Constructor Summary

    Constructors
    Constructor
    Description
    ChiSquareTest(DataSet dataSet, double alpha)
    Constructs a test using the given data set and significance level.

  • Method Summary

    Modifier and Type
    Method
    Description
    ChiSquareTest.Result
    calcChiSquare(int[] testIndices)
    Calculates chi square for a conditional crosstabulation table for independence question 0 _||_ 1 | 2, 3, ...max by summing up chi square and degrees of freedom for each conditional table in turn, where rows or columns that consist entirely of zeros have been removed.
    double
    getAlpha()
     
    CellTable
    getCellTable()
     
    DataSet
    getDataSet()
     
    int[]
    getDims()
     
    boolean
    isDetermined(int[] testIndices, double p)
     
    int[]
    selectFromArray(int[] arr, int[] indices)
     
    void
    setAlpha(double alpha)
    Sets the significance level to be used for tests.

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

  • Constructor Details

    • ChiSquareTest

      public ChiSquareTest(DataSet dataSet, double alpha)
      Constructs a test using the given data set and significance level.
      Parameters:
      dataSet - A data set consisting entirely of discrete variables.
      alpha - The significance level, usually 0.05.

  • Method Details

    • calcChiSquare

      public ChiSquareTest.Result calcChiSquare(int[] testIndices)
      Calculates chi square for a conditional crosstabulation table for independence question 0 _||_ 1 | 2, 3, ...max by summing up chi square and degrees of freedom for each conditional table in turn, where rows or columns that consist entirely of zeros have been removed.

    • isDetermined

      public boolean isDetermined(int[] testIndices, double p)
      Parameters:
      testIndices - An array of indices for variables in the dataset supplied in the constructor.
      p - The probability that some marginal for some table dominates. A good value is 0.99.
      Returns:
      True if the variable at index 0 is determined by the variables at the other indices.

    • getAlpha

      public double getAlpha()
      Returns:
      the getModel significance level being used for tests.

    • setAlpha

      public void setAlpha(double alpha)
      Sets the significance level to be used for tests.

    • selectFromArray

      public int[] selectFromArray(int[] arr, int[] indices)

    • getDataSet

      public DataSet getDataSet()

    • getDims

      public int[] getDims()

    • getCellTable

      public CellTable getCellTable()