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May 2018 Bayesian analysis of multiple-inflation Poisson models and its application to infection data
Duchwan Ryu, Devrim Bilgili, Önder Ergönül, Nader Ebrahimi
Braz. J. Probab. Stat. 32(2): 239-261 (May 2018). DOI: 10.1214/16-BJPS340

Abstract

In this article we propose a multiple-inflation Poisson regression to model count response data containing excessive frequencies at more than one non-negative integer values. To handle multiple excessive count responses, we generalize the zero-inflated Poisson regression by replacing its binary regression with the multinomial regression, while Su et al. [Statist. Sinica 23 (2013) 1071–1090] proposed a multiple-inflation Poisson model for consecutive count responses with excessive frequencies. We give several properties of our proposed model, and do statistical inference under the fully Bayesian framework. We perform simulation studies and also analyze the data related to the number of infections collected in five major hospitals in Turkey, using our methodology.

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Duchwan Ryu. Devrim Bilgili. Önder Ergönül. Nader Ebrahimi. "Bayesian analysis of multiple-inflation Poisson models and its application to infection data." Braz. J. Probab. Stat. 32 (2) 239 - 261, May 2018. https://doi.org/10.1214/16-BJPS340

Information

Received: 1 March 2016; Accepted: 1 October 2016; Published: May 2018
First available in Project Euclid: 17 April 2018

zbMATH: 06914674
MathSciNet: MR3787753
Digital Object Identifier: 10.1214/16-BJPS340

Rights: Copyright © 2018 Brazilian Statistical Association

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Vol.32 • No. 2 • May 2018
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