Empirical likelihood for partial linear models

被引：1
|
作者：
Qi-Hua Wang
Bing-Yi Jing
机构：
[1] Chinese Academy of Science,Academy of Mathematics and System Science
[2] China and Heilongjiang University,Department of Mathematics
[3] Hong Kong University of Science and Technology,undefined
来源：
Annals of the Institute of Statistical Mathematics | 2003年 / 55卷
关键词：
Empirical likelihood; partial linear model; Wilks' theorem;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper the empirical likelihood method due to Owen (1988,Biometrika,75, 237–249) is applied to partial linear random models. A nonparametric version of Wilks' theorem is derived. The theorem is then used to construct confidence regions of the parameter vector in the partial linear models, which has correct asymptotic coverage. A simulation study is conducted to compare the empirical likelihood and normal approximation based method.
引用
收藏
页码：585 / 595
页数：10
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