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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…
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…
Robust Retrospective Multiple Change-point Estimation for Multivariate Data
Alexandre Lung-Yut-Fong, Céline Lévy-Leduc, Olivier Cappé
We propose a non-parametric statistical procedure for detecting multiple change-points in multidimensional signals. The method is based on a test statistic that generalizes the wel…