Bayesian prediction for small areas using sur models |
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Authors: | Getachew Asfaw Dagne S James Press |
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Institution: | 1. Department of Epidemiology and Biostatistics , University of South Florida , Tampa, FL, 33612;2. Department of Statistics , University of California, Riverside , Riverside, CA, 92521 |
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Abstract: | Sample surveys are usually designed and analyzed to produce estimates for larger areas and/or populations. Nevertheless, sample sizes are often not large enough to give adequate precision for small area estimates of interest. To circumvent such difficulties, borrowing strength from related small areas via modeling becomes essential. In line with this, we propose a hierarchical multivariate Bayes prediction method for small area estimation based on the seemingly unrelated regressions (SUR) model. The performance of the proposed method was evaluated through simulation studies. |
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Keywords: | Hierarchical Bayes prediction random effects multivariate small area estimation Gibbs sampler |
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