  An extensive body of literature exists that specifically addresses the
univariate case of zero-inflated count models. In contrast, research pertaining
to multivariate models is notably less developed. We proposed two new
parsimonious multivariate models which can be used to model correlated
multivariate overdispersed count data. Furthermore, for different parameter
settings and sample sizes, various simulations are performed. In conclusion, we
demonstrated the performance of the newly proposed multivariate candidates on
two benchmark datasets, which surpasses that of several alternative approaches.
