anacjesus wrote:Hi,
I am analyzing a 28 years of data for grey seal females (297 individuals) sighted in 5 locations of an island (regions A, B, C, D and E). I want to see if regions where animals are sighted have an influence on their site-fidelity.
I am using a multi-state model for recaptures only. After inserting data into MARK a thousand of parameters is generated. Because it is impossible to run all selected models (too many parameters), I decided to run a model for each region's comparation fidelity, where I would have, for example, psi (A-B) time dependent, while making constant all the other variables (survival, recapture probability and all the other psi's). Then I would do this to psi (B-A), psi (C-A), psi (B-C), etc.
Thats because the default time-dependent model is over-parameterized for your data. If you have 5 states, and (say) 20 occasions, then you have *lots* of parameters to estimate, and unless you have relatively decent encounter probabilities (at the least), you're going to have trouble fitting a fully time-dependent model. Rather than assume that MARK is the problem, try running a starting model where all parameters are fixed over time. If you don't know how to do this, or why you might try this, then...(see last comment, below).
It is the only way I am thinking for testing this hypothesis.
Anyways, when I try to run this an error pops up: "Numerical convergence never reached, with maximum G=..."
Does any one have other ideas? Or know how to solve this error? I looked into MARK book but their advice didn't help much.
[So, why would a book about MARK tell you something about problems you have running M-SURGE?]
It seems that you have a number of basic misconceptions about fitting these sorts of models to your data. Whether you use MARK or M-SURGE to fit multi-state models is not the issue (for many of the models you're likely to be interested in, they'll do the same thing for you). I would suggest you step away from your data, and work through the first 7-8 chapters of the MARK book. Then, once you have a better understanding about models, model specification, estimation, and model selection, you can turn to your own data. Even if you ultimately use M-SURGE, the basic concepts introduced in the MARK book still apply.