Overdispersion : Models and estimation

@inproceedings{Hinde2003OverdispersionM,
  title={Overdispersion : Models and estimation},
  author={John Hinde and Clarice G. B. Dem},
  year={2003}
}
Overdispersion models for discrete data are considered and placed in a general framework. A distinction is made between completely specified models and those with only a mean-variance specification. Different formulations for the overdispersion mechanism can lead to different variance functions which can be placed within a general family. In addition, many different estimation methods have been proposed, including maximum likelihood, moment methods, extended quasi-likelihood, pseudo-likelihood… CONTINUE READING

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