Bivariate Zero-Inflated Generalized COM-Poisson Regression Model with Application

Count data often display excessive number of zero outcomes than are expected in the Poisson regression model. The zero-inflated Poisson regression model has been suggested to handle zero-inflated data. For bivariate and zero inflated cases, several regression models such as the bivariate zero-inflated Poisson (BZIP) have been considered. In this paper, we first introduce bivariate generalized Conway-Maxwell- Poisson regression model. Then we extend it to bivariate zero-inflated generalized Conway-Maxwell-Poisson regression model and calculate some of its properties. The proposed model was applied to a real data set. This model can be fitted to bivariate zero-inflated count data with positive or negative correlations and allow additional overdispersion of the two dependent variables.