73 citations · 140 across the 10 of their papers we have counts for
11 papers
Sign Consistency of the Generalized Elastic Net Estimator
Wencan Zhu, Eric Adjakossa, Céline Lévy-Leduc +1
In this paper, we propose a novel variable selection approach in the framework of high-dimensional linear models where the columns of the design matrix are highly correlated. It co…
A variable selection approach for highly correlated predictors in high-dimensional genomic data
Wencan Zhu, Céline Lévy-Leduc, Nils Ternès
In genomic studies, identifying biomarkers associated with a variable of interest is a major concern in biomedical research. Regularized approaches are classically used to perform…
Variable selection in sparse high-dimensional GLARMA models
Céline Lévy-Leduc, Sarah Ouadah, Laure Sansonnet
In this paper, we propose a novel variable selection approach in the framework of sparse high-dimensional GLARMA models. It consists in combining the estimation of the autoregressi…
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…
Improving heritability estimation by a variable selection approach in sparse high dimensional linear mixed models
Anna Bonnet, Céline Lévy-Leduc, Elisabeth Gassiat +2
Motivated by applications in neuroanatomy, we propose a novel methodology for estimating the heritability which corresponds to the proportion of phenotypic variance which can be ex…
Heritability estimation in high dimensional linear mixed models
Anna Bonnet, Elisabeth Gassiat, Céline Lévy-Leduc
Motivated by applications in genetic fields, we propose to estimate the heritability in high dimensional sparse linear mixed models. The heritability determines how the variance is…