Nonsubjective priors via predictive relative entropy regret

• 成果类型: Article
• 署名作者: Sweeting, Trevor J.; Datta, Gauri S.; Ghosh, Malay
• 署名单位: University of London; University College London; University System of Georgia; University of Georgia; State University System of Florida; University of Florida
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/009053605000000804
• 发表日期: 2006
• 页码: 441-468
• 关键词: bayes

摘要

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.