A new model for over-dispersed count data: Poisson quasi-Lindley regression model

Abstract

In this paper, a new regression model for count response variable is proposed via re-parametrization of Poisson quasi-Lindley distribution. The maximum likelihood and method of moment estimations are considered to estimate the unknown parameters of re-parametrized Poisson quasi-Lindley distribution. The simulation study is conducted to evaluate the efficiency of estimation methods. The real data set is analyzed to demonstrate the usefulness of proposed model against the well-known regression models for count data modeling such as Poisson and negative-binomial regression models. Empirical results show that when the response variable is over-dispersed, the proposed model provides better results than other competitive models.