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Title: A Bayesian approach to modeling the variances of estimates in small area estimation Authors:  Sirapat Watakajaturaphon - University of California, Davis (United States) [presenting]
Abstract: The estimates of variances in small area estimation play an important role. We discuss common problems of assuming a frequentist framework for modeling the variances of small area estimates and propose a new Bayesian framework to deal with these problems in practice. We propose suitable Markov chain Monte Carlo algorithms and study the theoretical properties of our proposed model. Finally, we implement our model in a real data set.