
Accession Number : ADA181356
Title : On the Convergence Rates of Empirical Bayes Rules for TwoAction Problems. Discrete Case.
Descriptive Note : Technical rept.,
Corporate Author : PURDUE UNIV LAFAYETTE IN DEPT OF STATISTICS
Personal Author(s) : Liang,Ta Chen
PDF Url : ADA181356
Report Date : Mar 1987
Pagination or Media Count : 16
Abstract : The purpose of this paper is to investigate the convergence rates of a sequence of empirical Bayes decision rules for the twoaction 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 existng empirical Bayes rules.
Descriptors : *CONVERGENCE, *BAYES THEOREM, *STATISTICAL DECISION THEORY, RATES, OPTIMIZATION, RISK
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE