I have a couple questions regarding occupancy analysis.
1) Given a particular design and sample size, how many parameters can I estimate without overfitting? For example, if I have 100 sites and 5 surveys at each site, how many parameters can I estimate in PRESENCE if the species was present at 80% of the sites with a detection probability of 0.8? Or what if I only observed my species at 10% of the 100 sites with a detection probability of 0.20, then how many parameters can I estimate?
2) If you have covariates with levels that have no detections, is this a problem? For example, I have a covariate for region, but my species was only seen in 2 of the 3 regions so for the 3rd region the detection history is all zeros. In logistic regression, this would be a problem. Is it a problem in occupancy analysis? I ran a couple simulations in PRESENCE to try and figure it out and in those simulations I found that if the covariate was used to model detection, it resulted in huge standard errors (like what would happen in logistic regression). But, if the covariate was used to model occupancy, it did not seem to have any problems.
Any insight on either of these questions would be greatly appreciated. Thank you.