on the stochastic minimization of sample size by the bechhofer-kulkarni bernoulli sequential selection procedure
作者:
C. Jennison,
期刊:
Sequential Analysis
(Taylor Available online 1989)
卷期:
Volume 8,
issue 3
页码: 281-291
ISSN:0747-4946
年代: 1989
DOI:10.1080/07474948908836182
出版商: Marcel Dekker, Inc.
关键词: k-population;Bernoulli selection problem;sequential selection procedure;adaptive sampling
数据来源: Taylor
摘要:
Bechhofer and Kulkarni (1982) proposed procedures for selecting that one ofkBernoulli populations with the largest single trial success probability. They showed that their procedure fork= 2 minimizes the expected total sample size amongst a class of procedures, all of which attain the same probability of correct selection. Kulkarni and Jennison (1986) generalized this result to the casek≥ 3. In this article we prove the stronger result that the Bechhofer-Kulkarni procedure for eachk≥2 stochastically minimizes the distribution of sample size amongst procedures in the same class. That is, the distribution of sample size for the Bechhofer-Kulkarni procedure is the same as or stochastically smaller than that for any other procedure in the class.
点击下载:
PDF (352KB)
返 回