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http://dx.doi.org/10.7465/jkdi.2012.23.4.749

M-quantile kernel regression for small area estimation  

Shim, Joo-Yong (Department of Data Science, Inje University)
Hwang, Chang-Ha (Department of Statistics, Dankook University)
Publication Information
Journal of the Korean Data and Information Science Society / v.23, no.4, 2012 , pp. 749-756 More about this Journal
Abstract
An approach widely used for small area estimation is based on linear mixed models. However, when the functional form of the relationship between the response and the input variables is not linear, it may lead to biased estimators of the small area parameters. In this paper we propose M-quantile kernel regression for small area mean estimation allowing nonlinearities in the relationship between the response and the input variables. Numerical studies are presented that show the sample properties of the proposed estimation method.
Keywords
Kernel regression; M-quantile; small area estimation; support vector quantile regression;
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Times Cited By KSCI : 4  (Citation Analysis)
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