Statistics Papers

Document Type

Journal Article

Date of this Version

2011

Publication Source

The Annals of Statistics

Volume

39

Issue

5

Start Page

2740

Last Page

2765

DOI

10.1214/11-AOS917

Abstract

For the normal linear model variable selection problem, we propose selection criteria based on a fully Bayes formulation with a generalization of Zellner’s g-prior which allows for p > n. A special case of the prior formulation is seen to yield tractable closed forms for marginal densities and Bayes factors which reveal new model evaluation characteristics of potential interest.

Keywords

Bayes factor, model selection consistency, ridge regression, singular value decomposition, variable selection

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Date Posted: 27 November 2017

This document has been peer reviewed.