3 papers
astro-ph.IM2020
Some detection tests for low complexity data models and unknown background distribution
D. Mary, S. Bourguignon, E. Roquain +2
We consider several detection situations where, under the alternative hypothesis, the signal admits a low complexity model and, under both the null and the alternative hypotheses,…
stat.ME2018
Estimation of large block structured covariance matrices: Application to "multi-omic" approaches to study seed quality
Marie Perrot-Dockès, Céline Lévy-Leduc, Loïc Rajjou
Motivated by an application in high-throughput genomics and metabolomics, we propose a novel, efficient and fully data-driven approach for estimating large block structured sparse…
math.ST2017
Variable selection in multivariate linear models with high-dimensional covariance matrix estimation
Marie Perrot-Dockès, Céline Lévy-Leduc, Laure Sansonnet +1
In this paper, we propose a novel variable selection approach in the framework of multivariate linear models taking into account the dependence that may exist between the responses…