Package org.hipparchus.stat.inference

Class OneWayAnova

java.lang.Object
org.hipparchus.stat.inference.OneWayAnova
public class OneWayAnova extends Object
Implements one-way ANOVA (analysis of variance) statistics.

Tests for differences between two or more categories of univariate data (for example, the body mass index of accountants, lawyers, doctors and computer programmers). When two categories are given, this is equivalent to the TTest.

Uses the Hipparchus F Distribution implementation to estimate exact p-values.

This implementation is based on a description at One way Anova (dead link)

 Abbreviations: bg = between groups,
                wg = within groups,
                ss = sum squared deviations

  • Constructor Details

    • OneWayAnova

      public OneWayAnova()
      Empty constructor.

      This constructor is not strictly necessary, but it prevents spurious javadoc warnings with JDK 18 and later.

      Since:
      3.0

  • Method Details

    • anovaFValue

      public double anovaFValue(Collection<double[]> categoryData) throws MathIllegalArgumentException, NullArgumentException
      Computes the ANOVA F-value for a collection of double[] arrays.

      Preconditions:

      • The categoryData Collection must contain double[] arrays.
      • There must be at least two double[] arrays in the categoryData collection and each of these arrays must contain at least two values.

      This implementation computes the F statistic using the definitional formula

         F = msbg/mswg

      where

        msbg = between group mean square
  mswg = within group mean square

      are as defined here

      Parameters:
      categoryData - Collection of double[] arrays each containing data for one category
      Returns:
      Fvalue
      Throws:
      NullArgumentException - if categoryData is null
      MathIllegalArgumentException - if the length of the categoryData array is less than 2 or a contained double[] array does not have at least two values

    • anovaPValue

      public double anovaPValue(Collection<double[]> categoryData) throws MathIllegalArgumentException, NullArgumentException, MathIllegalStateException
      Computes the ANOVA P-value for a collection of double[] arrays.

      Preconditions:

      • The categoryData Collection must contain double[] arrays.
      • There must be at least two double[] arrays in the categoryData collection and each of these arrays must contain at least two values.

      This implementation uses the Hipparchus F Distribution implementation to estimate the exact p-value, using the formula

         p = 1 - cumulativeProbability(F)

      where F is the F value and cumulativeProbability is the Hipparchus implementation of the F distribution.

      Parameters:
      categoryData - Collection of double[] arrays each containing data for one category
      Returns:
      Pvalue
      Throws:
      NullArgumentException - if categoryData is null
      MathIllegalArgumentException - if the length of the categoryData array is less than 2 or a contained double[] array does not have at least two values
      MathIllegalStateException - if the p-value can not be computed due to a convergence error
      MathIllegalStateException - if the maximum number of iterations is exceeded

    • anovaPValue

      public double anovaPValue(Collection<StreamingStatistics> categoryData, boolean allowOneElementData) throws MathIllegalArgumentException, NullArgumentException, MathIllegalStateException
      Computes the ANOVA P-value for a collection of StreamingStatistics.

      Preconditions:

      • The categoryData Collection must contain StreamingStatistics.
      • There must be at least two StreamingStatistics in the categoryData collection and each of these statistics must contain at least two values.

      This implementation uses the Hipparchus F Distribution implementation to estimate the exact p-value, using the formula

         p = 1 - cumulativeProbability(F)

      where F is the F value and cumulativeProbability is the Hipparchus implementation of the F distribution.

      Parameters:
      categoryData - Collection of StreamingStatistics each containing data for one category
      allowOneElementData - if true, allow computation for one catagory only or for one data element per category
      Returns:
      Pvalue
      Throws:
      NullArgumentException - if categoryData is null
      MathIllegalArgumentException - if the length of the categoryData array is less than 2 or a contained StreamingStatistics does not have at least two values
      MathIllegalStateException - if the p-value can not be computed due to a convergence error
      MathIllegalStateException - if the maximum number of iterations is exceeded

    • anovaTest

      public boolean anovaTest(Collection<double[]> categoryData, double alpha) throws MathIllegalArgumentException, NullArgumentException, MathIllegalStateException
      Performs an ANOVA test, evaluating the null hypothesis that there is no difference among the means of the data categories.

      Preconditions:

      • The categoryData Collection must contain double[] arrays.
      • There must be at least two double[] arrays in the categoryData collection and each of these arrays must contain at least two values.
      • alpha must be strictly greater than 0 and less than or equal to 0.5.

      This implementation uses the Hipparchus F Distribution implementation to estimate the exact p-value, using the formula

         p = 1 - cumulativeProbability(F)

      where F is the F value and cumulativeProbability is the Hipparchus implementation of the F distribution.

      True is returned iff the estimated p-value is less than alpha.

      Parameters:
      categoryData - Collection of double[] arrays each containing data for one category
      alpha - significance level of the test
      Returns:
      true if the null hypothesis can be rejected with confidence 1 - alpha
      Throws:
      NullArgumentException - if categoryData is null
      MathIllegalArgumentException - if the length of the categoryData array is less than 2 or a contained double[] array does not have at least two values
      MathIllegalArgumentException - if alpha is not in the range (0, 0.5]
      MathIllegalStateException - if the p-value can not be computed due to a convergence error
      MathIllegalStateException - if the maximum number of iterations is exceeded