Asymptotic efficiency of some nonparametric tests for location on hyperspheres

Sophie Dabo-Niang, Baba Thiam and Thomas Verdebout

Statistics & Probability Letters, 2022, vol. 188, issue C

Abstract: In the present paper, we show that several classical nonparametric tests for multivariate location in the Euclidean case can be adapted to nonparametric tests for the location problem on hyperspheres. The tests we consider are spatial signed-rank tests for location on hyperspheres. We compute the asymptotic powers of the latter tests in the classical rotationally symmetric case. In particular, we show that the spatial signed-rank test uniformly dominates the spatial sign test and has performances that are extremely close to the asymptotically optimal test in the well-known von Mises–Fisher case. Monte-Carlo simulations confirm our asymptotic results.

Keywords: Directional statistics; Location tests; Spatial signed-ranks (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1016/j.spl.2022.109524

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