Class KolmogorovSmirnov

  • Direct Known Subclasses:
    KolmogorovSmirnov1Sample, KolmogorovSmirnov2Samples

    public abstract class KolmogorovSmirnov
    extends HypothesisTest
    The Kolmogorov-Smirnov test (KS test) compares a sample with a reference probability distribution (one-sample KS test), or to compare two samples (two-sample KS test). The Kolmogorov-Smirnov statistic quantifies the distance between the empirical distribution function of the sample and the cumulative distribution function of the reference distribution (one-sample KS test), or between the empirical distribution functions of two samples (two-sample KS test). The null distribution of this statistic is calculated under the null hypothesis that the sample is drawn from the reference distribution (in the one-sample case), or that the samples are drawn from the same distribution (in the two-sample case). In each case, the distributions considered under the null hypothesis are continuous distributions but are otherwise unrestricted. The test-statistics is either Dn, Dn+, or Dn-, depending on the side to compute.

    By R convention, when the exact p-value is not available, we use the limiting distribution. The exact p-value is not available in the case of ties for the one-sample case.

    The R equivalent function is ks.test.

    See Also: