Variable Selection in Linear Mixed Models Using an Extended Class of Penalties

DOI10.1111/j.1467-842X.2012.00687.xzbMath1334.62119OpenAlexW1973671840MaRDI QIDQ2802814

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Publication date: 27 April 2016

Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1467-842x.2012.00687.x

zbMATH Keywords

linear mixed modelsvariable selectionLASSOpenalised likelihood

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Paired and multiple comparisons; multiple testing (62J15)

Related Items (5)

Model selection in linear mixed-effect models ⋮ On the estimation of variance parameters in non-standard generalised linear mixed models: application to penalised smoothing ⋮ A simultaneous variable selection methodology for linear mixed models ⋮ Non-concave penalization in linear mixed-effect models and regularized selection of fixed effects ⋮ A note on model selection using information criteria for general linear models estimated using REML

Uses Software

• R
• SemiPar
• glmnet

Cites Work

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• Unnamed Item
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