An interval estimation procedure with deterministic stopping rule in Bayes sequential interval estimation

機構典藏 > College of Sciences > Graduate Institute & Department of Mathematics > Journal Article > Item 987654321/41457

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Title:	An interval estimation procedure with deterministic stopping rule in Bayes sequential interval estimation
Authors:	黃連成;Hwang, Leng-cheng;Yang, Chia-chen
Contributors:	淡江大學數學學系
Keywords:	Asymptotically Bayes;Asymptotically pointwise optimal;Bayes sequential interval estimation;Stopping rule
Date:	2001-04-15
Issue Date:	2010-01-28 07:37:13 (UTC+8)
Publisher:	Elsevier
Abstract:	The problem of Bayes sequential interval estimation of the mean of a normal distribution with known variance is considered. An interval estimation procedure, which does not depend on the prior distribution, with deterministic stopping rule is proposed in this paper. It is shown that the proposed procedure is asymptotically pointwise optimal and asymptotically Bayes in the sense of Bickel and Yahav (Proceedings of the Fifth Berkeley Symposium on Mathematics and Statistical Probability, Vol. 1, University of California Press, California, 1967, pp. 401–413; Ann. Math. Statist. 39 (1968) 442–456.) for a large class of prior distributions.
Relation:	Statistics and Probability Letters 52(3), pp.243-248
DOI:	10.1016/S0167-7152(00)00196-6
Appears in Collections:	[Graduate Institute & Department of Mathematics] Journal Article

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