The multivariate multisample nonparametric rank statistics for the location alternatives

  • Hidetoshi Murakami Tokyo University of Science

Abstract

Multisample testing problems are among the most important topics in nonparametric statistics. Various nonparametric tests have been proposed for multisample testing problems involving location parameters, and the analysis of multivariate data is important in many scientific fields. One type of multivariate multisample testing problem based on Jureckova-Kalina-type rank of distance is discussed in this paper. A multivariate Kruskal-Wallis-type statistic is proposed for testing the location parameter with both equal and unequal sample sizes. Simulations are used to compare the power of proposed nonparametric statistics with the Wilks' lambda, the Pillai's trace and the Lawley-Hotelling trace for various population distributions.

 

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Author Biography

Hidetoshi Murakami, Tokyo University of Science
Department of Mathematical Information Science
Published
2017-01-04
How to Cite
Murakami, H. (2017). The multivariate multisample nonparametric rank statistics for the location alternatives. Austrian Journal of Statistics, 46(1), 3-13. https://doi.org/10.17713/ajs.v46i1.130
Section
Articles