Inferência em distribuições discretas bivariadas

Abstract

The analysis of bivariate data can be found in several areas of knowledge, when the data of interest are obtained in a paired way and present correlation between counts. In this work the Holgate bivariate Poisson, bivariate generalized Poisson and bivariate zero-inflated Poisson models are presented, which are useful to the modeling of bivariate count data correlated. Illustrative applications are presented for these models and the comparison between them is made by using criteria of model selection AIC and BIC, as well as the asymptotic likelihood ratio test. Particularly, we propose a Bayesian approach to the Holgate bivariate Poisson and bivariate zero-inflated Poisson models, based in the Gibbs sampling algorithm with data augmentation.