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

页码：585 / 595

页数：10

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