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Kolmogorov-Smirnov two-sample test based on regression rank scores

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Abstract

We derive the two-sample Kolmogorov-Smirnov type test when a nuisance linear regression is present. The test is based on regression rank scores and provides a natural extension of the classical Kolmogorov-Smirnov test. Its asymptotic distributions under the hypothesis and the local alternatives coincide with those of the classical test.

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Authors and Affiliations

  1. Faculty of Mathematics and Physics, Department of Probability and Statistics, Charles University in Prague, Sokolovská 83, 186 75, Prague 8, Czech Republic

    Martin Schindler

  2. Technical University in Liberec, Studentská 2, 461 17, Liberec 1, Czech Republic

    Martin Schindler

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  1. Martin Schindler
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Correspondence to Martin Schindler.

Additional information

(Supplement to the special issue of Appl. Math. 53 (2008), No. 3)

This work was supported by the Czech Science Foundation under Grant No. 201/05/H007 and by Research Project LC06024.

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Schindler, M. Kolmogorov-Smirnov two-sample test based on regression rank scores. Appl Math 53, 297–304 (2008). https://doi.org/10.1007/s10492-008-0027-8

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  • DOI: https://doi.org/10.1007/s10492-008-0027-8

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