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CPS1823 Ishapathik D. et al.
                  the doubly inflated multivariate Poisson model provides significantly better fit
                  over multivariate Poisson model. So, we get a significantly better fit using the
                  doubly inflated multivariate Poisson models instead of using the multivariate
                  Poisson model which ignores the information of the inflation in the respective
                  cells for this data.

                  5.    Summary
                      In this paper, we studied regression method for multivariate count data
                  having inflations in two cells. The responses are assumed to follow a doubly
                  inflated multivariate Poisson distribution. A method to find a probability mass
                  function for a  doubly  inflated  multivariate Poisson  random variate  using  a
                  Gaussian  copula  is  described  and  an  algorithm  to  estimate  the  unknown
                  parameters  of  the  model  using  the  MLE  is  also  provided.  The  proposed
                  method  is  illustrated  using  a  real  data  containing  multivariate  count  data
                  having inflation in two cells. We observe that the regression using the doubly
                  inflated multivariate Poisson model provides significantly better fit over the
                  multivariate Poisson model ignoring the cells inflation in the data with respect
                  to the AIC criteria.

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