Abstract: For the problem of the quality monitoring and counting of excessive gas emissions in chemical industry parks, a generalized zero-inflated binomial distribution model is constructed. Statistics show that the times of number of excessive gas emissions has a typical zero-inflated feature. The traditional zero-inflated Poisson model and negative binomial regression model and so on will underestimate the probability of zero inflation. A generalized zero-inflated binomial distribution model is constructed by extending the traditional binomial regression model to a more general form. This model satisfies the characteristic that the expectation is less than the variance, and better solves the problems of both over-dispersed and zero-inflated in excessive gas emissions. Experiments show that the generalized zero-flated binomial distribution model has a good fitting effect, strong adaptability and robustness.

Key words: count model, generalized binomial distribution, zero-inflated model, zero-inflated binomial regression model, air quality analysis