The COM-Poisson Model for Count Data: A Survey of Methods and Applications

TitleThe COM-Poisson Model for Count Data: A Survey of Methods and Applications
Publication TypeJournal Article
Year of Publication2012
AuthorsSellers, K. F., S. Borle, and G. Shmueli
JournalApplied Stochastic Models in Business and Industry
Volume28
Issue2
Pages104-116
Abstract

The Poisson distribution is a popular distribution for modeling count data, yet it is constrained by its equi-dispersion assumption, making it less than ideal for modeling real data that often exhibit over- or under-dispersion. The COM-Poisson distribution is a two-parameter generalization of the Poisson distribution that allows for a wide range of over- and under-dispersion. It not only generalizes the Poisson distribution, but also contains the Bernoulli and geometric distributions as special cases. This distribution‟s flexibility and special properties has prompted a fast growth of methodological and applied research in various fields. This paper surveys the different COM-Poisson models that have been published thus far, and their applications in areas including marketing, transportation, and biology, among others.

URLhttp://onlinelibrary.wiley.com/doi/10.1002/asmb.918/abstract
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