The use of hurdle models are often motivated by an excess of zeroes in the data, that is not sufficiently accounted for in more standard statistical models.
Hurdle models were later developed for count data, with Poisson, geometric,[2] and negative binomial[3] models for the non-zero counts .
With a mixture model, the probability of the variable being zero is determined by both the main distribution function
Specifically, a zero-inflated model for a random variable x is where
is the mixture weight that determines the amount of zero-inflation.