Empirical likelihood in a semi-parametric model

被引：1
|
作者：
Qin, J [1 ]
Wong, A [1 ]
机构：
[1] YORK UNIV,DEPT MATH & STAT,N YORK,ON M3J 1P3,CANADA
来源：
SCANDINAVIAN JOURNAL OF STATISTICS | 1996年 / 23卷 / 02期
关键词：
empirical likelihood; Lagrange multiplier; robustness; semi-parametric model; Wilks' theorem;
D O I：
暂无
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：
Sometimes we cannot specify a statistical model in a parametric form completely, For example, we might assume that a random variable has a distribution that is roughly normal in the centre of the distribution but with tails that are arbitrary, We might then be interested in inference for the mean of the distribution, using methods that are insensitive to the shape of the tails. In this paper, we define the semi-parametric likelihood function. We show that the semi-parametric likelihood ratio statistic has asymptotically a chi-squared distribution. Some simulation results are presented.
引用
收藏
页码：209 / 219
页数：11
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