The Annals of Statistics
- Ann. Statist.
- Volume 12, Number 2 (1984), 751-757.
A Note on Selecting Parametric Models in Bayesian Inference
This note is concerned with how to replace assessment of a "true" prior on a nonparametric family of distributions--which is usually infeasible--by assessment of an approximating prior with support in a parametrized subfamily, in such a way that the posterior derived from the parametric model is close to the "true" posterior. In general it is not sufficient that the approximating prior be close to the true prior in the sense of weak convergence, and we characterize the additional aspect of the true prior that must be considered explicitly.
Ann. Statist., Volume 12, Number 2 (1984), 751-757.
First available in Project Euclid: 12 April 2007
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Krasker, William S. A Note on Selecting Parametric Models in Bayesian Inference. Ann. Statist. 12 (1984), no. 2, 751--757. doi:10.1214/aos/1176346521. https://projecteuclid.org/euclid.aos/1176346521