Statistics Papers

Document Type

Journal Article

Date of this Version

10-2010

Publication Source

IMS Collections: Borrowing Strength: Theory Powering Applications - A. Festschrift for Lawrence D. Brown

Volume

6

Start Page

158

Last Page

165

DOI

10.1214/10-IMSCOLL611

Abstract

For the general Bayesian model uncertainty framework, the focus of this paper is on the development of model space priors which can compensate for redundancy between model classes, the so-called dilution priors proposed in George (1999). Several distinct approaches for dilution prior construction are suggested. One is based on tessellation determined neighborhoods, another on collinearity adjustments, and a third on pairwise distances between models.

Copyright/Permission Statement

The original and published work is available at: https://projecteuclid.org/euclid.imsc/1288099018#abstract

Keywords

Model averaging, model selection, objective Bayes, prior distribution, variable selection

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Date Posted: 27 November 2017

This document has been peer reviewed.