Accession Number : ADA181356

Title :   On the Convergence Rates of Empirical Bayes Rules for Two-Action 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 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 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