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Minimum MSE regression estimator with estimated population quantities of auxiliary variables

Authors
Park, MingueCho, HyungJun
Issue Date
15-12월-2008
Publisher
ELSEVIER
Citation
COMPUTATIONAL STATISTICS & DATA ANALYSIS, v.53, no.2, pp.394 - 404
Indexed
SCIE
SCOPUS
Journal Title
COMPUTATIONAL STATISTICS & DATA ANALYSIS
Volume
53
Number
2
Start Page
394
End Page
404
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/122219
DOI
10.1016/j.csda.2008.08.003
ISSN
0167-9473
Abstract
Construction of a regression estimator in which the population means of auxiliary variables are estimated with a larger sample is considered. Using the variances of the estimated population means, and the correlation between auxiliary variables and the variable of interest, a design consistent regression estimator that has minimum model mean squared error under a working model is derived. A limited simulation study shows that the minimum model mean squared error regression estimator performs well compared to the generalized least squares regression estimator, even when the working model is inappropriate. (C) 2008 Elsevier B.V. All rights reserved.
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CHO, HYUNG JUN
정경대학 (통계학과)
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