Open Access
December 1995 On convergence of posterior distributions
Subhashis Ghosal, Jayanta K. Ghosh, Tapas Samanta
Ann. Statist. 23(6): 2145-2152 (December 1995). DOI: 10.1214/aos/1034713651

Abstract

Z.A general (asymptotic) theory of estimation was developed by Ibragimov and Has’minskii under certain conditions on the normalized likelihood ratios. In an earlier work, the present authors studied the limiting behaviour of the posterior distributions under the general setup of Ibragimov and Has’minskii. In particular, they obtained a necessary condition for the convergence of a suitably centered (and normalized) posterior to a constant limit in terms of the limiting likelihood ratio process. In this paper, it is shown that this condition is also sufficient to imply the posterior convergence. Some related results are also presented.

Citation

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Subhashis Ghosal. Jayanta K. Ghosh. Tapas Samanta. "On convergence of posterior distributions." Ann. Statist. 23 (6) 2145 - 2152, December 1995. https://doi.org/10.1214/aos/1034713651

Information

Published: December 1995
First available in Project Euclid: 15 October 2002

zbMATH: 0858.62024
MathSciNet: MR1389869
Digital Object Identifier: 10.1214/aos/1034713651

Subjects:
Primary: 62F15 , 62F25

Keywords: asymptotics , Bayes estimates , Bernstein-von Mises theorem , convergence of posterior , likelihood ratio process

Rights: Copyright © 1995 Institute of Mathematical Statistics

Vol.23 • No. 6 • December 1995
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