Robust inference strategy in the presence of measurement error

被引：8
|
作者：
Ahmed, S. Ejaz [1 ]
Hussein, Abdulkadir [1 ]
Nkurunziza, Severien [1 ]
机构：
[1] Univ Windsor, Dept Math & Stat, Windsor, ON N9B 3P4, Canada
来源：
STATISTICS & PROBABILITY LETTERS | 2010年 / 80卷 / 7-8期
基金：
加拿大自然科学与工程研究理事会;
关键词：
EMPIRICAL LIKELIHOOD;
D O I：
10.1016/j.spl.2009.12.031
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：
In this paper, we consider a statistical model where samples are subject to measurement errors. Further, we propose a shrinkage estimation strategy by using the maximum empirical likelihood estimator (MELE) as the base estimator. Our asymptotic results clearly demonstrate the superiority of our proposed shrinkage strategy over the MELE. Monte Carlo simulation results show that such a performance still holds in finite samples. We apply our method to real data set. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码：726 / 732
页数：7
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