A note on model selection using information criteria for general linear models estimated using REML

DOI10.1111/anzs.12254zbMath1420.62020OpenAlexW2921881736WikidataQ128227445 ScholiaQ128227445MaRDI QIDQ5234443

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Publication date: 26 September 2019

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

Full work available at URL: https://doi.org/10.1111/anzs.12254

zbMATH Keywords

model selectionAkaike information criterionBayesian information criterionAICBICREMLlinear mixed modelgeneral linear modelsresidual maximum likelihood

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Statistical ranking and selection procedures (62F07) Statistical aspects of information-theoretic topics (62B10)

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Uses Software

• R
• ASReml

Cites Work

• Model selection in linear mixed models
• Estimating the dimension of a model
• Unifying the derivations for the Akaike and corrected Akaike information criteria.
• Variable Selection in Linear Mixed Models Using an Extended Class of Penalties
• The Analysis of Designed Experiments and Longitudinal Data by Using Smoothing Splines
• Regression and time series model selection using variants of the schwarz information criterion
• Bayesian Measures of Model Complexity and Fit
• Bayes Factors
• Recovery of inter-block information when block sizes are unequal
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