Empirical likelihood confidence intervals for the endpoint of a distribution function

被引：11
|
作者：
Li, Deyuan [2 ]
Peng, Liang [1 ]
Qi, Yongcheng [3 ]
机构：
[1] Georgia Inst Technol, Sch Math, Atlanta, GA 30332 USA
[2] Fudan Univ, Dept Stat, Sch Management, Shanghai 200433, Peoples R China
[3] Univ Minnesota, Dept Math & Stat, Duluth, MN 55812 USA
来源：
TEST | 2011年 / 20卷 / 02期
关键词：
Confidence interval; Coverage probability; Empirical likelihood method; Endpoint; MAXIMUM; ESTIMATOR; PARAMETER; INDEX;
D O I：
10.1007/s11749-010-0204-4
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：
Estimating the endpoint of a distribution function is of interest in product analysis and predicting the maximum lifetime of an item. In this paper, we propose an empirical likelihood method to construct a confidence interval for the endpoint. A simulation study shows the proposed confidence interval has better coverage accuracy than the normal approximation method, and bootstrap calibration improves the accuracy.
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页码：353 / 366
页数：14
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