Open Access
Translator Disclaimer
June 2015 Bayesian Model Selection Based on Proper Scoring Rules
A. Philip Dawid, Monica Musio
Bayesian Anal. 10(2): 479-499 (June 2015). DOI: 10.1214/15-BA942

Abstract

Bayesian model selection with improper priors is not well-defined because of the dependence of the marginal likelihood on the arbitrary scaling constants of the within-model prior densities. We show how this problem can be evaded by replacing marginal log-likelihood by a homogeneous proper scoring rule, which is insensitive to the scaling constants. Suitably applied, this will typically enable consistent selection of the true model.

Citation

Download Citation

A. Philip Dawid. Monica Musio. "Bayesian Model Selection Based on Proper Scoring Rules." Bayesian Anal. 10 (2) 479 - 499, June 2015. https://doi.org/10.1214/15-BA942

Information

Published: June 2015
First available in Project Euclid: 4 February 2015

zbMATH: 1335.62017
MathSciNet: MR3420890
Digital Object Identifier: 10.1214/15-BA942

Rights: Copyright © 2015 International Society for Bayesian Analysis

JOURNAL ARTICLE
21 PAGES


SHARE
Vol.10 • No. 2 • June 2015
Back to Top