Nonsubjective priors via predictive relative entropy regret
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.
Cite
@article{arxiv.math/0605609,
title = {Nonsubjective priors via predictive relative entropy regret},
author = {Trevor J. Sweeting and Gauri S. Datta and Malay Ghosh},
journal= {arXiv preprint arXiv:math/0605609},
year = {2007}
}
Comments
Published at http://dx.doi.org/10.1214/009053605000000804 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)