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Negative Binomial Sujatha Distribution and its Applications in Analysis of Overdispersed Count Data

Publication Type : Conference Proceedings

Publisher : International Conference on Advances in Pure and Applied Mathematics.

Source : International Conference on Advances in Pure and Applied Mathematics, ICPAM 2018, vol. 7. 2018.

Campus : Coimbatore

School : School of Engineering

Department : Mathematics

Year : 2018

Abstract : 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.

Cite this Research Publication : K. M. Sakthivel, Rajitha C. S., and Rajkumar J., “Negative Binomial Sujatha Distribution and its Applications in Analysis of Overdispersed Count Data”, International Conference on Advances in Pure and Applied Mathematics, ICPAM 2018, vol. 7. 2018.

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