A Lower Confidence Bound on the Probability of a Correct Selection
作者:
Woo-Chul Kim,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1986)
卷期:
Volume 81,
issue 396
页码: 1012-1017
ISSN:0162-1459
年代: 1986
DOI:10.1080/01621459.1986.10478366
出版商: Taylor & Francis Group
关键词: Selection problem;Indifference zone approach;Retrospective analysis;Location parameter;Monotone likelihood ratio
数据来源: Taylor
摘要:
In the problem of selecting the best ofkpopulations, a natural rule is to select the population corresponding to the largest sample value of an appropriate statistic. As a retrospective analysis, a conservative lower confidence bound on the probability of a correct selection is derived when the probability density function has the monotone likelihood ratio property under the location parameter setting. The result is applied to the normal populations with both known and unknown common variance. Tables to implement the confidence bound are provided.
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