Selection of fixed effects in high dimensional linear mixed models using a multicycle ECM algorithm

DOI10.1016/j.csda.2014.06.022zbMath1506.62156OpenAlexW4295237805MaRDI QIDQ1623713

Magali San Cristobal, Florian Rohart, Béatrice Laurent

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2014.06.022

zbMATH Keywords

multiple hypothesis testinglinear mixed modelhigh dimensionlmmlasso

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)

Related Items (9)

A SAEM algorithm for fused Lasso penalized nonlinear mixed effect models: application to group comparison in pharmacokinetics ⋮ A graphical model selection tool for mixed models ⋮ Partial least square based approaches for high-dimensional linear mixed models ⋮ A general framework for penalized mixed-effects multitask learning with applications on DNA methylation surrogate biomarkers creation ⋮ Fixed Effects Testing in High-Dimensional Linear Mixed Models ⋮ Model selection in linear mixed-effect models ⋮ Fast Monte Carlo Markov chains for Bayesian shrinkage models with random effects ⋮ MMS ⋮ Non-concave penalization in linear mixed-effect models and regularized selection of fixed effects

Uses Software

• R

Cites Work

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