A Bayesian approach to sequential estimation without using the prior information

淡江大學機構典藏 > 理學院 > 數學學系暨研究所 > 期刊論文 > Item 987654321/41445

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题名:	A Bayesian approach to sequential estimation without using the prior information
其它题名:	無母數經驗貝氏方法之序列估計
作者:	黃連成;Hwang, Leng-cheng
贡献者:	淡江大學數學學系
关键词:	asymptotically Bayes;asymptotically non-deficient;asymptotically pointwise optimal;empirical Bayes
日期:	1997-11
上传时间:	2010-01-28 07:35:16 (UTC+8)
出版者:	Taylor & Francis
摘要:	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.
關聯:	Sequential Analysis 16(4), pp.319-343
DOI:	10.1080/07474949708836391
显示于类别:	[數學學系暨研究所] 期刊論文

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