Generalized fiducial inference on the mean of zero-inflated Poisson and Poisson hurdle models

Abstract Zero-inflated and hurdle models are widely applied to count data possessing excess zeros, where they can simultaneously model the process from how zeros were generated potentially help mitigate effects of overdispersion relative assumed distribution. Which use depends on generated: zero-inflated add an additional probability mass zero, while two-part comprised a degenerate distribution for zero-truncated Developing confidence intervals such is challenging since no closed-form function available calculate mean. In this study, generalized fiducial inference used construct means Poisson models. The proposed methods assessed by intensive simulation study. An illustrative example demonstrates methods.