A Kolmogorov-Smirnov Test for r Samples
| Autor: | Walter Böhm, Kurt Hornik |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Algebra and Number Theory
Weak convergence Mathematical analysis Asymptotic distribution Kolmogorov–Smirnov test Empirical distribution function Theoretical Computer Science symbols.namesake Computational Theory and Mathematics Sample size determination Chi-square test Test statistic Null distribution symbols Information Systems Mathematics |
| Zdroj: | Fundamenta Informaticae. 117:103-125 |
| ISSN: | 0169-2968 |
| DOI: | 10.3233/fi-2012-690 |
| Popis: | We consider the problem of testing whether r ≥ 2 samples are drawn from the same continuous distribution F(x). The test statistic we will study in some detail is defined as the maximum of the circular differences of the empirical distribution functions, a generalization of the classical 2-sample Kolmogorov-Smirnov test to r ≥ 2 independent samples. For the case of equal sample sizes we derive the exact null distribution by counting lattice paths confined to stay in the scaled alcove ${\cal A}$r of the affine Weyl group Ar−1. This is done using a generalization of the classical reflection principle. By a standard diffusion scaling we derive also the asymptotic distribution of the test statistic in terms of a multivariate Dirichlet series. When the sample sizes are not equal the reflection principle no longer works, but we are able to establish a weak convergence result even in this case showing that by a proper rescaling a test statistic based on a linear transformation of the circular differences of the empirical distribution functions has the same asymptotic distribution as the test statistic in the case of equal sample sizes. |
| Databáze: | OpenAIRE |
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