I am currently working a some datasets with count data in R, in which the response is the number of activities of a given type that were performed in one day by a population.
For each type, I build a Poisson model and test for over/underdispersion using the function
dispersiontest() from package
AER. Depending on the result, I switch to quasi-Poisson model when there is evidence of over- or underdispersion.
In a next step, I would like to sample and generate simulated data using the results of my models. If I have a Poisson model, I can use
lambda being the fitted value of the model. However, I have no idea how to do it in the cases of over/underdispersion. Any ideas?