On Distribution-Free Tests for the Multivariate Two-Sample Location-Scale Model
In this paper, we propose simple exact procedures for testing both a location shift and/or a scale change between two multivariate distributions. Our tests are strictly distribution-free and can be made either scale invariant or rotation invariant. Our approach combines a generalization of the Wilcoxon test based on projections of the data onto the first principal component, a generalization of the Siegel-Tukey test based on the concept of data depth, and a bivariate test for the location problem proposed by K. V. Mardia (1967, J. Roy. Statist. Soc. Ser. B29, 320-342). In addition, we show that the limiting null distribution of a test statistic proposed by R. Y. Liu and K. Singh (1993, J. Amer. Statist. Assoc.88, 252-260) does not depend on the depth considered.
Year of publication: |
2002
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Authors: | Rousson, Valentin |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 80.2002, 1, p. 43-57
|
Publisher: |
Elsevier |
Keywords: | data depth multivariate orderings nonparametric methods principal component analysis rank tests |
Saved in:
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