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

被引:0
|
作者
Hwang, LC [1 ]
Yang, CC [1 ]
机构
[1] Tamkang Univ, Dept Math, Taipei 25137, Taiwan
关键词
asymptotically bayes; asymptotically pointwise optimal; Bayes sequential interval estimation; stopping rule;
D O I
10.1016/S0167-7152(00)00196-6
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
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. Tt 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) 442-46.) for a large class of prior distributions. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:243 / 248
页数:6
相关论文
共 50 条