Regularization in regression: comparing Bayesian and frequentist methods in a poorly informative situation

DOI10.1214/12-BA716zbMath1330.62284arXiv1010.0300WikidataQ60461477 ScholiaQ60461477MaRDI QIDQ2633918

Jean-Michel Marin, Gilles Celeux, Mohammed El Anbari, Christian P. Robert Robert

Publication date: 5 February 2016

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1010.0300

zbMATH Keywords

calibrationregularization methodsnoninformative priorsmodel choiceDantzig selectorLassoelastic netZellner's \(g\)-prior

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Bayesian inference (62F15)

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