Package org.apache.commons.math3.distribution

Class KolmogorovSmirnovDistribution

java.lang.Object
org.apache.commons.math3.distribution.KolmogorovSmirnovDistribution
All Implemented Interfaces:
Serializable
public class KolmogorovSmirnovDistribution extends Object implements Serializable
Deprecated.
to be removed in version 4.0 - use KolmogorovSmirnovTest
Implementation of the Kolmogorov-Smirnov distribution.

Treats the distribution of the two-sided P(D_n < d) where D_n = sup_x |G(x) - G_n (x)| for the theoretical cdf G and the empirical cdf G_n.

This implementation is based on [1] with certain quick decisions for extreme values given in [2].

In short, when wanting to evaluate P(D_n < d), the method in [1] is to write d = (k - h) / n for positive integer k and 0 <= h < 1. Then P(D_n < d) = (n! / n^n) * t_kk, where t_kk is the (k, k)'th entry in the special matrix H^n, i.e. H to the n'th power.

References:

Note that [1] contains an error in computing h, refer to MATH-437 for details.

See Also:

  • Constructor Summary

    Constructors
    Constructor
    Description
    KolmogorovSmirnovDistribution(int n)
    Deprecated.
     

  • Method Summary

    Modifier and Type
    Method
    Description
    double
    cdf(double d)
    Deprecated.
    Calculates P(D_n < d) using method described in [1] with quick decisions for extreme values given in [2] (see above).
    double
    cdf(double d, boolean exact)
    Deprecated.
    Calculates P(D_n < d) using method described in [1] with quick decisions for extreme values given in [2] (see above).
    double
    cdfExact(double d)
    Deprecated.
    Calculates P(D_n < d) using method described in [1] with quick decisions for extreme values given in [2] (see above).

    Methods inherited from class java.lang.Object

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

  • Constructor Details

  • Method Details

    • cdf

      public double cdf(double d) throws MathArithmeticException
      Deprecated.
      Calculates P(D_n < d) using method described in [1] with quick decisions for extreme values given in [2] (see above). The result is not exact as with cdfExact(double) because calculations are based on double rather than BigFraction.
      Parameters:
      d - statistic
      Returns:
      the two-sided probability of P(D_n < d)
      Throws:
      MathArithmeticException - if algorithm fails to convert h to a BigFraction in expressing d as (k - h) / m for integer k, m and 0 <= h < 1.

    • cdfExact

      public double cdfExact(double d) throws MathArithmeticException
      Deprecated.
      Calculates P(D_n < d) using method described in [1] with quick decisions for extreme values given in [2] (see above). The result is exact in the sense that BigFraction/BigReal is used everywhere at the expense of very slow execution time. Almost never choose this in real applications unless you are very sure; this is almost solely for verification purposes. Normally, you would choose cdf(double)
      Parameters:
      d - statistic
      Returns:
      the two-sided probability of P(D_n < d)
      Throws:
      MathArithmeticException - if algorithm fails to convert h to a BigFraction in expressing d as (k - h) / m for integer k, m and 0 <= h < 1.

    • cdf

      public double cdf(double d, boolean exact) throws MathArithmeticException
      Deprecated.
      Calculates P(D_n < d) using method described in [1] with quick decisions for extreme values given in [2] (see above).
      Parameters:
      d - statistic
      exact - whether the probability should be calculated exact using BigFraction everywhere at the expense of very slow execution time, or if double should be used convenient places to gain speed. Almost never choose true in real applications unless you are very sure; true is almost solely for verification purposes.
      Returns:
      the two-sided probability of P(D_n < d)
      Throws:
      MathArithmeticException - if algorithm fails to convert h to a BigFraction in expressing d as (k - h) / m for integer k, m and 0 <= h < 1.