Zero-inflated distributions are assumed when count observations are characterised
by an excess frequency of zero. This study utilises the cubic rank transmutation map to extend
the exponential distribution and obtain a new mixing distribution. The distribution is then
used to obtain a new mixed Poisson distribution and its zero-inflated form. Different momentbased
mathematical properties of the mixed Poisson distributions and their zero-inflated forms
are presented. Five count data sets with varying percentages of zero counts are assessed with
new propositions and with both Poisson and negative binomial distributions (along with their
respective zero-inflated forms). Performance is compared using both –2LL and chi-square
goodness of fit. The new proposition outperforms both Poisson and negative binomial
distributions (and their zero-inflated forms). Results also reveal that zero-inflated forms of the
new proposition are inferior to their classical form. In most cases the classical negative
binomial distribution also provides a better fit than its zero-inflated form while the zeroinflated
Poisson distribution outperforms the Poisson distribution. In conclusion, most mixed
Poisson distributions exhibit the ability to effectively model the observations with excess zero
and tend to provide a better fit to the count observations with excess zero than their zeroinflated
forms.