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December, 1988 On the Convergence Rates of Empirical Bayes Rules for Two-Action Problems: Discrete Case
TaChen Liang
Ann. Statist. 16(4): 1635-1642 (December, 1988). DOI: 10.1214/aos/1176351058

Abstract

The purpose of this paper is to investigate the convergence rates of a sequence of empirical Bayes decision rules for the two-action decision problems where the distributions of the observations belong to a discrete exponential family. It is found that the sequence of the empirical Bayes decision rules under study is asymptotically optimal, and the order of associated convergence rates is $O(\exp(-cn))$, for some positive constant $c$, where $n$ is the number of accumulated past experience (observations) at hand. Two examples are provided to illustrate the performance of the proposed empirical Bayes decision rules. A comparison is also made between the proposed empirical Bayes rules and some earlier existing empirical Bayes rules.

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TaChen Liang. "On the Convergence Rates of Empirical Bayes Rules for Two-Action Problems: Discrete Case." Ann. Statist. 16 (4) 1635 - 1642, December, 1988. https://doi.org/10.1214/aos/1176351058

Information

Published: December, 1988
First available in Project Euclid: 12 April 2007

zbMATH: 0653.62007
MathSciNet: MR964943
Digital Object Identifier: 10.1214/aos/1176351058

Subjects:
Primary: 62C12

Rights: Copyright © 1988 Institute of Mathematical Statistics

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Vol.16 • No. 4 • December, 1988
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