I'm working on Pradel recruitment models. The time varying model is strongly supported, with 23 of 25 parameters estimable. All of the beta estimates for f(t) have standard errors of zero, except one of the times which has a standard error of -400 to 400. When I add a time parameter to phi, the standard errors are estimated for f.
So there are obviously some major problems with the most favored model. I've checked TFM and tried to search the forum but haven't found much except that standard errors of zero indicate a problem with the model. So three questions:
1. How do I troubleshoot where the problem might be in the model structure?
2. Are there some ways to constrain time that might allow the standard errors to be estimated?
3. Why would complicating model structure, going from 25 to 35 parameters, allow standard error to be estimated?
I appreciate any advice on this. Thank you.