Fast selection of nonlinear mixed effect models using penalized likelihood

DOI10.1016/j.csda.2021.107373OpenAlexW3208793219MaRDI QIDQ2072413

Edouard Ollier

Publication date: 26 January 2022

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

Full work available at URL: https://arxiv.org/abs/2103.01621

zbMATH Keywords

model selectionparticle swarm optimizationpenalized likelihoodnonlinear mixed effects modelsstochastic proximal gradient

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• UNLocBoX
• EGO
• AdaGrad

Cites Work

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• Random Effects Selection in Linear Mixed Models
• Coupling a stochastic approximation version of EM with an MCMC procedure
• Using the SAEM algorithm for mechanistic joint models characterizing the relationship between nonlinear PSA kinetics and survival in prostate cancer patients
• On perturbed proximal gradient algorithms
• Discussion: One-step sparse estimates in nonconcave penalized likelihood models

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