Asymptotic theory for the MLE from randomly censored exponential samples

被引：0
|
作者：
WANG Qihua Department of Probability and Statistics
机构：
来源：
Science Bulletin | 1998年 / 13期
关键词：
maximum likelihood estimate; Edgeworth expansion; bootstrap approximation; asymptotic minimax efficiency; law of iterated logarithm;
D O I：
暂无
中图分类号：
O212 [数理统计];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
The MLE of the parameter of the exponential population from the censored observations is considered. The Edgeworth expansions for the Studentized MLE are established by representing the relevant statistic as a U\|statistic plus a remainder. A semiparametric bootstrap method is introduced to the random censored model and the accuracy of bootstrap approximation of the MLE is investigated. Furthermore, it is shown that the MLE is asymptotically minimax efficient.
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页码：1071 / 1076
页数：6
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