Nonparametric tests for the general multivariate multi-sample problem

Caiya Zhang, Zhengyan Lin and Jianjun Wu

Journal of Nonparametric Statistics, 2009, vol. 21, issue 7, 877-888

Abstract: Some nonparametric tests for the multivariate multi-sample problem are proposed in this paper. For the location–scale model, the univariate Kruskal–Wallis test and the bivariate Mardia test are generalised to the multivariate case. For the general multivariate multi-sample problem, a new test based on the Liu-Singh statistic is proposed and the asymptotic null distribution of this test statistic is established under some regularity conditions. The results of simulation show that these tests are more effective than the parametric tests when the assumption of multivariate normal distribution is violated, especially under the scale model or the location–scale model.

Date: 2009
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DOI: 10.1080/10485250903111684

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