Jackknife Empirical Likelihood

被引：176

作者：

Jing, Bing-Yi ^{[1
]}

Yuan, Junqing

Zhou, Wang ^{[2
]}

机构：

[1] Hong Kong Univ Sci & Technol, Dept Math, Hong Kong, Hong Kong, Peoples R China

[2] Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore 117546, Singapore

来源：

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION | 2009年 / 104卷 / 487期

关键词：

Confidence regions; Empirical likelihood; Jackknife; Pseudo-values; U-statistics; CONFIDENCE-INTERVALS; U-STATISTICS; BIAS;

D O I：

10.1198/jasa.2009.tm08260

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：

Empirical likelihood has been found very useful in many different occasions. However, when applied directly to some more complicated statistics such as U-statistics, it runs into serious computational difficulties. In this paper, we introduce a so-called jackknife empirical likelihood (JEL) method. The new method is extremely simple to use in practice. In particular. the JEL is shown to be very effective in handling one and two-sample U-statistics. The JEL can be potentially useful for other nonlinear statistics.

引用

页码：1224 / 1232

页数：9

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