The COM-Poisson model for count data: a survey of methods and applications

@article{Sellers2012TheCM,
  title={The COM-Poisson model for count data: a survey of methods and applications},
  author={Kimberly F. Sellers and S. Borle and Galit Shmueli},
  journal={Applied Stochastic Models in Business and Industry},
  year={2012},
  volume={28},
  pages={104-116}
}
  • Kimberly F. Sellers, S. Borle, Galit Shmueli
  • Published 2012
  • Computer Science
  • Applied Stochastic Models in Business and Industry
  • 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… CONTINUE READING

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