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Activity Number: 347 - Computationally Intensive Bayesian Methodology
Type: Contributed
Date/Time: Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #307210 Presentation
Title: Order-Restricted Bayesian Estimation of Multinomial Counts for Small Areas
Author(s): Xinyu Chen* and Balgobin Nandram
Companies: Worcester Polytechnic Institute and Worcester Polytechnic Institute
Keywords: Bayesian computation; Gibbs sample; Multinomial counts; Monte Carlo Integration; Unimodal order restrictions

We consider making inference about several small areas with data obtained in the form of multino- mial counts. The cell probabilities have the same unimodal order restriction across areas, and these cell probabilities share a common effect. Therefore, a hierarchical multinomial-Dirichlet model, used to model the cell probabilities and the cell counts, allows a borrowing of strength across areas. We used the Gibbs sampler to make inference about the order-restricted multinomial parameters. We show how to perform the computations because there are difficulties poised by the order re- strictions. An application on body mass index showed that the order restriction is necessary and it provides increased precision over the scenario without the restriction.

Authors who are presenting talks have a * after their name.

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