The COM-Poisson model for count data: A survey of methods and applications
Sellers, K F and Borle, S and Shmueli, G (2012) The COM-Poisson model for count data: A survey of methods and applications. Applied Stochastic Models in Business and Industry, 28 (2). pp. 104-116.
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The Poisson distribution is a popular distribution for modeling count data, yet it is constrained by its equidispersion assumption, making it less than ideal for modeling real data that often exhibit over-dispersion or under-dispersion. The COM-Poisson distribution is a two-parameter generalization of the Poisson distribution that allows for a wide range of over-dispersion 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 have 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. Copyright © 2011 John Wiley & Sons, Ltd.
| ISB Creiators: |
ISB Creators ORCiD Shmueli, G UNSPECIFIED |
|---|---|
| Item Type: | Article |
| Additional Information: | biology; Conway-Maxwell-Poisson; marketing; overdispersion; regression model; transportation; underdispersion |
| Subjects: | Applied Statistics and Computing |
| Depositing User: | Users 13 not found. |
| Date Deposited: | 29 Nov 2014 11:52 |
| Last Modified: | 29 Nov 2014 11:52 |
| URI: | http://eprints.exchange.isb.edu/id/eprint/343 |
| Publisher URL: | http://dx.doi.org/10.1002/asmb.918 |
| Publisher OA policy: | http://www.sherpa.ac.uk/romeo/issn/1524-1904/ |
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