Double Generalized Beta-Binomial and Negative Binomial Regression Models-Reference-Cited by-同舟云学术

Double Generalized Beta-Binomial and Negative Binomial Regression Models

Published:2017-01-16 Issue:1 Volume:40 Page:141-163
ISSN:2389-8976
Container-title:Revista Colombiana de Estadística
language:
Short-container-title:Rev. colomb. estad.

Author:

Cepeda-Cuervo Edilberto,Cifuentes-Amado María Victoria

Abstract

Overdispersion is a common phenomenon in count datasets, that can greatly affect inferences about the model. In this paper develop three joint mean and dispersion regression models in order to fit overdispersed data. These models are based on reparameterizations of the beta-binomial and negative binomial distributions. Finally, we propose a Bayesian approach to estimate the parameters of the overdispersion regression models and use it to fit a school absenteeism dataset.

Publisher

Universidad Nacional de Colombia

Subject

Statistics and Probability

Reference18 articles.

1. Breslow, N. (1984), ‘Extra-Poisson variation in Log-Linear models’, Journal of Applied Statistics 31, 38–44.

2. Cepeda-Cuervo, E. (2001), Modelagem da Variabilidade em Modelos Lineares Generalizados, Unpublished Math Ph.D. thesis, Mathematics Institute, Universidade Federal do Río de Janeiro.

3. Cepeda-Cuervo, E. & Achcar, J. (2009), ‘Modelos de regresión heterocedásticos usando aproximación bayesiana’, Revista Colombiana de Estadística 32(2), 267–287.

4. Cepeda-Cuervo, E. & Gamerman, D. (2005), ‘Bayesian methodology for modeling parameters in the two parameter exponential family’, Revista Estadística 57(168-169), 93–105.

5. Cepeda-Cuervo, E., Migon, H., Garrido, L. & Achcar, J. (2014), ‘Generalized linear models with random effects in the two-parameter exponential family’, Journal of Statistical Computation and Simulation 84(3), 513–525.

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