Some connections between Bayesian and non-Bayesian methods for regression model selection

Faming Liang

Statistics & Probability Letters, 2002, vol. 57, issue 1, 53-63

Abstract: In this article, we study the connections between Bayesian methods and non-Bayesian methods for variable selection in multiple linear regression. We show that each of the non-Bayesian criteria, FPE[alpha], AIC, Cp and adjusted , has its Bayesian correspondence under an appropriate prior setting. The theoretical results are illustrated by numerical simulations.

Keywords: Bayes; factor; FPE[alpha]; criterion; Kullback-Leibler; distance; MAP; Variable; selection (search for similar items in EconPapers)
Date: 2002
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