TESTING EXPONENTIALITY AGAINST IDMRL DISTRIBUTIONS WITH UNKNOWN CHANGE POINT
成果类型：
Article
署名作者：
HAWKINS, DL; KOCHAR, S; LOADER, C
署名单位：
Indian Statistical Institute; Indian Statistical Institute Delhi; AT&T; Nokia Corporation; Nokia Bell Labs
刊物名称：
ANNALS OF STATISTICS
ISSN/ISSBN：
0090-5364
DOI：
10.1214/aos/1176348522
发表日期：
1992
页码：
280-290
关键词：
摘要：
Guess, Hollander and Proschan proposed tests for exponentiality versus IDMRL (increasing initially and then decreasing mean residual life) distributions when the change point, or corresponding quantile, is known. In this paper we propose two tests which do not require such knowledge of the change point. The tests are based on estimates of functionals of the cdf which discriminate between the exponential and IDMRL families.
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