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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Abstract

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 Creators:	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/
Related URLs:	Link to full-text (other repositories) Link to full-text (other repositories) Google Scholar

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