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A non-parametric test for several independent samples. (English) Zbl 1216.62066
Summary: We introduce a large sample nonparametric test for the hypothesis of equal distributions of three or more independent samples. The test can be considered as a generalisation of the two sample run tests of A. Wald and J. Wolfowitz [Ann. Math. Stat. 11, 147–162 (1940; Zbl 0023.24802)] in that it sorts the data and replaces the values with the ‘label’ of the sample from which they come, thus transforming the problem to a question about the randomness of the resulting pooled sample. The test statistic and its asymptotic null distribution are derived using the central limit theorem of finite Markov chains. Simulation results and comparisons with the standard \(k\)-sample Kruskal-Wallis and Kolmogorov-Smirnov tests are given. One particular strength of the test is that it is capable of distinguishing between different distributions having the same mean in a few cases when the Kruskal-Wallis test is completely paralysed.

MSC:
62G10 Nonparametric hypothesis testing
62E20 Asymptotic distribution theory in statistics
65C60 Computational problems in statistics (MSC2010)
60F05 Central limit and other weak theorems
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