Dynamic network models based on the Generalized Poisson distribution capture unequal dispersion in temporal count data for improved fit and prediction.
Graphical inspection of Figures B.1-B.2 reveals convergence to the true parameter values and a good mixing of the MCMC chains
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Generalized Poisson Dynamic Network Models
Dynamic network models based on the Generalized Poisson distribution capture unequal dispersion in temporal count data for improved fit and prediction.