bizicount: Bivariate Zero-Inflated Count Copula Regression Using R

John M. Niehaus, Lin Zhu, Scott J. Cook, Mikyoung Jun

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Abstract

Two common issues arise in regression modelling of bivariate count data: (i) dependence across outcomes, and (ii) excess zero counts (i.e., zero inflation). However, there are currently few options to estimate bivariate zero-inflated count regression models in R. Therefore, we present an R package, bizicount, that enables researchers to easily estimate bivariate zero-inflated count copula regression models. By using copulas to model the dependence across outcomes, researchers do not have to make assumptions about the multivariate (and zero-inflated) structure relating their count variables to one another. Instead, they are only required to make familiar assumptions about the marginal distribution of each outcome variable, which should enable wider use of our approach. Below we present our proposed estimator, detail its advantages over existing alternatives, and demonstrate the use of the corresponding functions for bivariate modeling of terrorism data from Nigeria.

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