3 papers
stat.ME2020
Variable selection in sparse GLARMA models
M. Gomtsyan, C. Lévy-Leduc, S. Ouadah +1
In this paper, we propose a novel and efficient two-stage variable selection approach for sparse GLARMA models, which are pervasive for modeling discrete-valued time series. Our ap…
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…
math.ST2016
Nonparametric homogeneity tests and multiple change-point estimation for analyzing large Hi-C data matrices
Vincent Brault, Sarah Ouadah, Laure Sansonnet +1
We propose a novel nonparametric approach for estimating the location of block boundaries (change-points) of non-overlapping blocks in a random symmetric matrix which consists of r…