Abstract
Zero-inflated and hurdle models are widely applied to count data possessing excess zeros, where they can simultaneously model the process from how the zeros were generated and potentially help mitigate the effects of overdispersion relative to the assumed count distribution. Which model to use depends on how the zeros are generated: zero-inflated models add an additional probability mass on zero, while hurdle models are two-part models comprised of a degenerate distribution for the zeros and a zero-truncated distribution. Developing confidence intervals for such models is challenging since no closed-form function is available to calculate the mean. In this study, generalized fiducial inference is used to construct confidence intervals for the means of zero-inflated Poisson and Poisson hurdle models. The proposed methods are assessed by an intensive simulation study. An illustrative example demonstrates the inference methods.
Document Type
Article
Publication Date
3-6-2021
Digital Object Identifier (DOI)
https://doi.org/10.1186/s40488-021-00117-0
Related Content
The UTI data are reported in the text. Simulation scripts for the results presented are available upon request from the authors.
Repository Citation
Zou, Yixuan; Hannig, Jan; and Young, Derek S., "Generalized Fiducial Inference on the Mean of Zero-Inflated Poisson and Poisson Hurdle Models" (2021). Statistics Faculty Publications. 31.
https://uknowledge.uky.edu/statistics_facpub/31
Notes/Citation Information
Published in Journal of Statistical Distributions and Applications, v. 8, article no. 5.
© The Author(s) 2021
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