Article (Scientific journals)
On testing the equality of latent roots of scatter matrices under ellipticity
BERNARD, Gaspard; Verdebout, Thomas
2024In Journal of Multivariate Analysis, 199, p. 105232
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Keywords :
Elliptical distributions; Hypothesis testing; Latent roots; Statistics and Probability; Numerical Analysis; Statistics, Probability and Uncertainty
Abstract :
[en] In the present paper, we tackle the problem of testing H0q:λq>λq+1=⋯=λp, where λ1,…,λp are the scatter matrix eigenvalues of an elliptical distribution on Rp. This is a classical problem in multivariate analysis which is very useful in dimension reduction. We analyse the problem using the Le Cam asymptotic theory of experiments and show that contrary to the testing problems on eigenvalues and eigenvectors of a scatter matrix tackled in Hallin et al. (2010), the non-specification of nuisance parameters has an asymptotic cost for testing H0q. We moreover derive signed-rank tests for the problem that enjoy the property of being asymptotically distribution-free under ellipticity. The van der Waerden rank test uniformly dominates the classical pseudo-Gaussian procedure for the problem. Numerical illustrations show the nice finite-sample properties of our tests.
Disciplines :
Mathematics
Author, co-author :
BERNARD, Gaspard ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Mathematics (DMATH)
Verdebout, Thomas;  ECARES and Mathematics Department, Université libre de Bruxelles (ULB), Brussels, Belgium
External co-authors :
yes
Language :
English
Title :
On testing the equality of latent roots of scatter matrices under ellipticity
Publication date :
January 2024
Journal title :
Journal of Multivariate Analysis
ISSN :
0047-259X
eISSN :
1095-7243
Publisher :
Academic Press Inc.
Volume :
199
Pages :
105232
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
Horizon 2020 Framework Programme
Fédération Wallonie-Bruxelles
Horizon 2020
Horizon 2020
Fonds De La Recherche Scientifique - FNRS
Funding text :
Thomas Verdebout's research is supported by an ARC grant of the Communauté Française de Belgique and a Projet de Recherche (PDR) from the Fonds National de la Recherche Scientifique (FNRS). This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 811017.
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