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:: Volume 15, Issue 2 (3-2022) ::
JSS 2022, 15(2): 463-480 Back to browse issues page
Robust Empirical Bayes Small Area Estimation with Symmetric α-Stable Distribution for Error Components
Shaho Zarei *
Abstract:   (2716 Views)

The most widely used model in small area estimation is the area level or the Fay-Herriot model. In this model, it is typically assumed that both the area level random effects (model errors) and the sampling errors have a Gaussian distribution.  However, considerable variations in error components (model errors and sampling errors) can cause poor performance in small area estimation. In this paper, to overcome this problem, the symmetric α-stable distribution is used to deal with outliers in the error components. The model parameters are estimated with the empirical Bayes method. The performance of the proposed model is investigated in different simulation scenarios and compared with the existing classic and robust empirical Bayes methods. The proposed model can improve estimation results, in particular when both error components are normal or have heavy-tailed distribution.

Keywords: Small Area Estimation, Area Level Model, Empirical Bayes, α-Stable Distribution.
Full-Text [PDF 249 kb]   (1226 Downloads)    
Type of Study: Applied | Subject: Official Statistics
Received: 2021/01/3 | Accepted: 2022/03/1 | Published: 2021/10/4
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Zarei S. Robust Empirical Bayes Small Area Estimation with Symmetric α-Stable Distribution for Error Components. JSS 2022; 15 (2) :463-480
URL: http://jss.irstat.ir/article-1-746-en.html

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 15, Issue 2 (3-2022) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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