JSM 2004 - Toronto

Abstract #301428

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Activity Number: 414
Type: Contributed
Date/Time: Thursday, August 12, 2004 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract - #301428
Title: Asymptotic Admissibility and Bayesian Estimation
Author(s): John W. Emerson*+
Companies: Yale University
Address: PO Box 208290, New Haven, CT, 06520,
Keywords: Bayesian ; asymptotic ; admissibility
Abstract:

Hartigan (1998) shows that when the maximum likelihood prior fails to exist, the maximum likelihood estimator is asymptotically inadmissible in Kullback-Leibler risk. However, no explicit asymptotic estimator beating maximum likelihood is exhibited. We propose a method of discovering a discrete least favorable prior leading to a continuous prior and corresponding Bayes estimator "near to'' and yet improving on maximum likelihood with respect to Kullback-Leibler loss.

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