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A test for independence of two multivariate samples

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Abstract

The paper presents a new nonparametric test for independence of two vectors. The idea is based on zonotope approach by G. Koshevoy, H. Oja and others, see [4, 5]. Under the independence hypothesis the test statistic converges in distribution to the supremum of a certain Gaussian field, and its asymptotic distribution is found using the theory of extrema of random Gaussian fields developed by V. Piterbarg and Yu. Tyurin, see [6, 8]. In contrast to traditional correlation coefficients the formula is not symmetric.

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Authors and Affiliations

  1. Moscow State University, Moscow, Russia

    E. M. Sukhanova

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  1. E. M. Sukhanova
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Correspondence to E. M. Sukhanova.

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Sukhanova, E.M. A test for independence of two multivariate samples. Math. Meth. Stat. 17, 74–86 (2008). https://doi.org/10.3103/S1066530708010067

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  • DOI: https://doi.org/10.3103/S1066530708010067

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