A Bayesian approach to sequential estimation without using the prior information

機構典藏 > College of Sciences > Graduate Institute & Department of Mathematics > Journal Article > Item 987654321/41445

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Title:	A Bayesian approach to sequential estimation without using the prior information
Other Titles:	無母數經驗貝氏方法之序列估計
Authors:	黃連成;Hwang, Leng-cheng
Contributors:	淡江大學數學學系
Keywords:	asymptotically Bayes;asymptotically non-deficient;asymptotically pointwise optimal;empirical Bayes
Date:	1997-11
Issue Date:	2010-01-28 07:35:16 (UTC+8)
Publisher:	Taylor & Francis
Abstract:	The problem of Bayes sequential point estimation without using the prior information is considered. Two sequential procedures of the type of Bickel and Yahav (1967, 1968), for the scale exponential and location normal families respectively, are proposed. It is shown in the present paper that the proposed procedures are asymptotically pointwise optimal (A.P.O.) in the sense of Bickel and Yahav (1967) and the second order approximation of the Bayes risk is established for a large class of prior distributions.
Relation:	Sequential Analysis 16(4), pp.319-343
DOI:	10.1080/07474949708836391
Appears in Collections:	[Graduate Institute & Department of Mathematics] Journal Article

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