Empirical Bayes detection of a change in distribution

被引：3
|
作者：
Karunamuni, RJ
Zhang, SP
机构：
[1] Department of Mathematical Sciences, University of Alberta, Edmonton
来源：
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS | 1996年 / 48卷 / 02期
关键词：
empirical Bayes; change points; Bayes sequential rules; stopping times; statistical process control;
D O I：
10.1007/BF00054787
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 detection of a change in distribution is considered. Shiryayev (1963, Theory Probab. Appl., 8, pp. 22-46, 247-264 and 402-413; 1978, Optimal Stopping Rules, Springer, New York) solved the problem in a Bayesian framework assuming that the prior on the change point is Geometric (p) Shiryayev showed that the Bayes solution prescribes stopping as soon as the posterior probability of the change having occurred exceeds a fixed level. In this paper, a myopic policy is studied. An empirical. Bayes stopping time is investigated for detecting a change in distribution when the prior is not completely known.
引用
收藏
页码：229 / 246
页数：18
相关论文
共 50 条
12345