activity
20052026
most citedMultivariate quantiles and multiple-output regression quantiles: From optimization to halfspace depth

252 citations · 827 across the 31 of their papers we have counts for

collaborators
Showing math.STShow all

31 papers · 1 filter

math.ST2026

Möbius-Invariant Goodness-of-Fit Tests for the Spherical Cauchy Model

Diego Bolón, Davy Paindaveine

We introduce a class of goodness-of-fit tests for the spherical Cauchy model on the unit hypersphere. The proposed procedures exploit the invariance of the spherical Cauchy family…

math.ST2021

On the consistency of incomplete U-statistics under infinite second-order moments}

Alexander Dürre, Davy Paindaveine

We derive a consistency result, in the -sense, for incomplete U-statistics in the non-standard case where the kernel at hand has infinite second-order moments. Assuming that t…

math.ST2021★ 1 cited

On a class of Sobolev tests for symmetry of directions, their detection thresholds, and asymptotic powers

Eduardo García-Portugués, Davy Paindaveine, Thomas Verdebout

We consider a class of symmetry hypothesis testing problems including testing isotropy on and testing rotational symmetry on the hypersphere . For…

math.ST2020

On the behavior of extreme -dimensional spatial quantiles under minimal assumptions

Davy Paindaveine, Joni Virta

"Spatial" or "geometric" quantiles are the only multivariate quantiles coping with both high-dimensional data and functional data, also in the framework of multiple-output quantile…

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…