Accession Number : ADA313572
Title : Empirical Bayes Simultaneous Selection Procedures for Comparing Normal Populations with a Standard,
Descriptive Note : Technical rept.,
Corporate Author : PURDUE UNIV LAFAYETTE IN DEPT OF STATISTICS
Personal Author(s) : Gupta, Shanti S. ; Liang, TaChen
PDF Url : ADA313572
Report Date : MAY 1996
Pagination or Media Count : 24
Abstract : In this paper, we derive statistical selection procedures to partition k normal populations into 'good' or 'bad' ones, respectively, using the nonparametric empirical Bayes approach. The relative regret risk of a selection procedure is used as a measure of its performance. We establish the asymptotic optimality of the proposed empirical Bayes selection procedures and investigate the associated rates of convergence. Under a very mild condition, the proposed empirical Bayes selection procedures are shown to have rates of convergence of order close to O(k(-1/2)) where k is the number of populations involved in the selection problem. With further strong assumptions, the empirical Bayes selection procedures have rates of convergence of order O(k(-a(r-1)/(2r+1))) where 1 <a< 2 and r is an integer greater than 2.
Descriptors : *NONPARAMETRIC STATISTICS, *BAYES THEOREM, *POPULATION(MATHEMATICS), OPTIMIZATION, ANALYSIS OF VARIANCE, CONVERGENCE, STATISTICAL PROCESSES, ASYMPTOTIC NORMALITY, NORMAL DISTRIBUTION.
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE