Modelling count data with overdispersion and spatial effects

  title={Modelling count data with overdispersion and spatial effects},
  author={Susanne Gschl{\"o}\ssl and Claudia Czado},
In this paper we consider regression models for count data allowing for overdispersion in a Bayesian framework. We account for unobserved heterogeneity in the data in two ways. On the one hand, we consider more flexible models than a common Poisson model allowing for overdispersion in different ways. In particular, the negative binomial and the generalized Poisson distribution are addressed where overdispersion is modelled by an additional model parameter. Further, zero-inflated models in which… CONTINUE READING


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