I am trying to fit some presence-absence data for prairie species in the incidence function metapopulation model based on the paper by Quintana-Ascencio and Menges(1996). I am using SPSS and I have also tried using SAS. However I have been running into the following problems:
1. Some times the data fail to converge even after 500 iterations - this tells me that the species does not fit the model. Any comments? 2. Sometimes the data converge, but the standard error is greater than the values of the unknown variables. This is a big problem because that questions the very validity of the estimate. 3. Sometimes the data converge at two very different points depending on the parameter values. In this case, the question I have is, which one is correct? Is the one with less iteration the better answer, or the one with a smaller standard error? If anyone has done a non-linear regression(Levenberg-Marquardt) before and has some thoughts/comments/suggestions please let me know. Thank you. Suneeti Jog Post-Doctoral Associate Kansas Biological Survey University of Kansas Email:[EMAIL PROTECTED]
