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20122021
most citedOptimal rank-based testing for principal components

69 citations · 94 across the 5 of their papers we have counts for

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6 papers · 1 filter

math.ST2019

On the power of axial tests of uniformity on spheres

Christine Cutting, Davy Paindaveine, Thomas Verdebout

Testing uniformity on the -dimensional unit sphere is arguably the most fundamental problem in directional statistics. In this paper, we consider this problem in the framework o…

math.ST2019

Preliminary test estimation in ULAN models

Davy Paindaveine, Joséa Rasoafaraniaina, Thomas Verdebout

Preliminary test estimation, which is a natural procedure when it is suspected a priori that the parameter to be estimated might take value in a submodel of the model at hand, is a…

math.ST2019

Inference for spherical location under high concentration

Davy Paindaveine, Thomas Verdebout

Motivated by the fact that circular or spherical data are often much concentrated around a location , we consider inference about under "high concentration" asymptot…

math.ST2018

Sign tests for weak principal directions

Davy Paindaveine, Julien Remy, Thomas Verdebout

We consider inference on the first principal direction of a -variate elliptical distribution. We do so in challenging double asymptotic scenarios for which this direction eventu…

math.ST2013

Local powers of optimal one- and multi-sample tests for the concentration of Fisher-von Mises-Langevin distributions

Christophe Ley, Thomas Verdebout

One-sample and multi-sample tests on the concentration parameter of Fisher-von Mises-Langevin (FvML) distributions have been well studied in the literature. However, only very litt…

math.ST201269 cited

Optimal rank-based testing for principal components

Marc Hallin, Davy Paindaveine, Thomas Verdebout

This paper provides parametric and rank-based optimal tests for eigenvectors and eigenvalues of covariance or scatter matrices in elliptical families. The parametric tests extend t…