On small area estimation under a sub-area level model

被引:19
|
作者
Torabi, Mahmoud [1 ]
Rao, J. N. K. [2 ]
机构
[1] Univ Manitoba, Dept Community Hlth Sci, Winnipeg, MB R3E 0W3, Canada
[2] Carleton Univ, Sch Math & Stat, Ottawa, ON K1S 5B6, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Best linear unbiased prediction; Fay-Herriot model; Linear mixed models; Mean squared error; Variance components; MEAN SQUARED ERROR;
D O I
10.1016/j.jmva.2014.02.001
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
We propose an extension of the well-known Fay and Herriot (1979) area level model to sub-area level. Not only this model may be used to estimate small area means by borrowing strength from related areas, but also by borrowing strength from sub-areas to obtain more efficient sub-area estimators. Model-based empirical best linear unbiased prediction (EBLUP) estimators are obtained from the BLUP estimators by replacing the model parameters by suitable estimators, using an iterative method based on weighted residual sum of squares. Second order approximations to the mean squared error (MSE) of the EBLUP estimators are obtained and then used to drive MSE estimators unbiased to second order. Results of simulation studies on the performance of the proposed estimators are also provided. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码:36 / 55
页数:20
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