Improving heritability estimation by a variable selection approach in sparse high dimensional linear mixed models

A Bonnet, C Lévy-Leduc, E Gassiat… - Journal of the Royal …, 2018 - academic.oup.com
Motivated by applications in neuroanatomy, we propose a novel methodology to estimate
heritability, which corresponds to the proportion of phenotypic variance that can be explained …

Heritability estimation in high dimensional sparse linear mixed models

A Bonnet, E Gassiat, C Lévy-Leduc - 2015 - projecteuclid.org
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 …

Heritability estimation in high dimensional linear mixed models

A Bonnet, E Gassiat, C Lévy-Leduc - arXiv preprint arXiv:1404.3397, 2014 - arxiv.org
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 …

Adaptive estimation of high-dimensional signal-to-noise ratios

N Verzelen, E Gassiat - 2018 - projecteuclid.org
… on the regime where p is large compared to n and where p logp ≤ n2. It turns out that no
estimator̂η can simultaneously achieve the minimax risk R ∗ (k) over all k = 1,...,p, and that …

[PDF][PDF] Heritability estimation in high dimensional sparse linear mixed models

ABE Gassiat, C Lévy-Leduc - imo.universite-paris-saclay.fr
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 …