EMPIRICAL BAYES RULES FOR SELECTING THE BEST EXPONENTIAL-POPULATION WITH LOCATION PARAMETER

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/27817

Title:	EMPIRICAL BAYES RULES FOR SELECTING THE BEST EXPONENTIAL-POPULATION WITH LOCATION PARAMETER
Authors:	LIN,IC;LEU,LY
Contributors:	統計研究所
Keywords:	NONEXPONENTIAL FAMILY
Date:	1994
Issue Date:	2010-06-29 19:34:17 (UTC+8)
Publisher:	中央大學
Abstract:	Among k(greater-than-or-equal-to 2) exponential populations with location parameters, we use the Empirical Bayes approach to select the best population. We first construct estimators for the unknown prior distribution. Then, the Bayes selection rule d(n) with respect to the estimated prior distribution is considered as the proposed empirical Bayes selection rule. We show the consistency of the estimated prior distribution and establish the asymptotic optimality of the rule d(n). Finally we give an illustrative example to implement the proposed procedure.
Relation:	COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Appears in Collections:	[Graduate Institute of Statistics] journal & Dissertation

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