I have a time series that count the number of "type 1" events in a city, for each day. The serie contains a lot of zeros because type 1 events are rare (about 80% of counts are zeros). I'm using a Poisson Model but I don't know how to handle temporal dependencies. For example, I know that there are some other events (let say "type 2") which will increase the probability of an event of type 1 in the current day and/or in the next days. The Poisson parameter is not constant over time.
Do you know a good R package to handle this and a good way to model this situation ?