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Small Area Estimation via Nonparametric Mixed Effects Model
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 Title & Authors
Small Area Estimation via Nonparametric Mixed Effects Model
Jeong, Seok-Oh; Shin, Key-Il;
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 Abstract
Small area estimation is a statistical inference method to overcome the large variance due to the small sample size allocated in a small area. Recently some nonparametric estimators have been applied to small area estimation. In this study, we suggest a nonparametric mixed effect small area estimator using kernel smoothing and compare the small area estimators using labor statistics.
 Keywords
Small area estimation;mixed effects model;nonparametric mixed effects model;kernel smoothing;
 Language
Korean
 Cited by
1.
비모수와 준모수 혼합모형을 이용한 소지역 추정,정석오;신기일;

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2.
소지역 실업률의 패널추정을 위한 일반화커널추정방정식,심주용;김영원;황창하;

Journal of the Korean Data and Information Science Society, 2013. vol.24. 6, pp.1199-1210 crossref(new window)
1.
Semiparametric and Nonparametric Mixed Effects Models for Small Area Estimation, Korean Journal of Applied Statistics, 2013, 26, 1, 71  crossref(new windwow)
2.
Generalized kernel estimating equation for panel estimation of small area unemployment rates, Journal of the Korean Data and Information Science Society, 2013, 24, 6, 1199  crossref(new windwow)
 References
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2.
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Wu, H. and Zhang, J.-T.(2006). Nonparametric Regression Methods for Longitudinal Data Analysis, John Wiley & Sons.