UCL logo

UCL Discovery

UCL home » Library Services » Electronic resources » UCL Discovery

Nonsubjective priors via predictive relative entropy regret

Sweeting, TJ; Datta, GS; Ghosh, M; (2006) Nonsubjective priors via predictive relative entropy regret. ANN STAT , 34 (1) 441 - 468. 10.1214/009053605000000804. Green open access

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
302Kb

Abstract

We explore the construction of nonsubjective prior distributions in Bayesian statistics via a posterior predictive relative entropy regret criterion. We carry out a minimax analysis based on a derived asymptotic predictive loss function and show that this approach to prior construction has a number of attractive features. The approach here differs from previous work that uses either prior or posterior relative entropy regret in that we consider predictive performance in relation to alternative nondegenerate prior distributions. The theory is illustrated with an analysis of some specific examples.

Type:Article
Title:Nonsubjective priors via predictive relative entropy regret
Open access status:An open access version is available from UCL Discovery
DOI:10.1214/009053605000000804
Keywords:nonsubjective Bayesian inference, predictive inference, relative entropy loss, higher-order asymptotics, PARTIAL INFORMATION, MODEL SELECTION, BAYES, DISTRIBUTIONS
UCL classification:UCL > School of BEAMS > Faculty of Maths and Physical Sciences > Statistical Science

View download statistics for this item

Archive Staff Only: edit this record