On Zero-Modified Poisson-Sujatha Distribution to Model Overdispersed Count Data

In this paper we propose the zero-modified Poisson-Sujatha distribution as an alternative to model overdispersed count data exhibiting inflation or deflation of zeros. It will be shown that the zero modification can be incorporated by using the zero-truncated Poisson-Sujatha distribution. A simple r...

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Bibliographic Details
Main Authors: Wesley Bertoli da Silva, Angélica Maria Tortola Ribeiro, Katiane Silva Conceição, Marinho Gomes Andrade, Francisco Louzada Neto
Format: Article
Language:English
Published: Austrian Statistical Society 2018-05-01
Series:Austrian Journal of Statistics
Online Access:http://www.ajs.or.at/index.php/ajs/article/view/590
Description
Summary:In this paper we propose the zero-modified Poisson-Sujatha distribution as an alternative to model overdispersed count data exhibiting inflation or deflation of zeros. It will be shown that the zero modification can be incorporated by using the zero-truncated Poisson-Sujatha distribution. A simple reparametrization of the probability function will allow us to represent the zero-modified Poisson-Sujatha distribution as a hurdle model. This trick leads to the fact that proposed model can be fitted without any previously information about the zero modification present in a given dataset. The maximum likelihood theory will be used for parameter estimation and asymptotic inference concerns. A simulation study will be conducted in order to evaluate some frequentist properties of the developed methodology. The usefulness of the proposed model will be illustrated using real datasets of the biological sciences field and comparing it with other models available in the literature.
ISSN:1026-597X