Title | The COM-Poisson Model for Count Data: A Survey of Methods and Applications |
Publication Type | Journal Article |
Year of Publication | 2012 |
Authors | Sellers, K. F., S. Borle, and G. Shmueli |
Journal | Applied Stochastic Models in Business and Industry |
Volume | 28 |
Issue | 2 |
Pages | 104-116 |
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. |
URL | http://onlinelibrary.wiley.com/doi/10.1002/asmb.918/abstract |
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COM-Poisson Survey | 581.27 KB |