Pseudo-empirical likelihood estimation using nonparametric regression

被引：1
|
作者：
Rueda, M. [1 ]
Munoz, J. F. [1 ]
机构：
[1] Univ Granada, Fac Ciencias, Dept Estadist & IO, E-18071 Granada, Spain
来源：
APPLIED MATHEMATICS LETTERS | 2009年 / 22卷 / 07期
关键词：
Sample surveys; Inclusion probabilities; Lagrange multiplier method; Regression estimator; Local polynomial regression; AUXILIARY INFORMATION; COMPLEX SURVEYS;
D O I：
10.1016/j.aml.2009.01.024
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Pseudo-empirical likelihood estimation of the population mean is considered. A nonparametric regression theory is proposed, to provide the fitted values on which to calibrate, and the common model misspecification problem is therefore addressed. Results derived from empirical studies show that the proposed estimator for the population mean can perform better than alternative estimators. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1021 / 1024
页数：4
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