Of course it is generally possible to generate datasets for a perfectly well-defined model that are hard to fit, but in this particular case I feel it should be possible. In my observations, glmm.admb is far more numerically stable fitting GLMM's than other software I've seen. Further , I don't think the data I generated come from a model that is overparameterized, severely contaminated with outliers, has no noise, or is nonlinear. But I encourage anyone to run a simulation study with generated data they think are acceptable and compare the robustness of several methods. I leave it at this.
Best regards, Roel de Jong Berton Gunter wrote: > May I interject a comment? > > >>When data is generated from a specified model with reasonable >>parameter >>values, it should be possible to fit such a model successful, >>or is this >>me being stupid? > > > Let me take a turn at being stupid. Why should this be true? That is, why > should it be possible to easily fit a model that is generated ( i.e. using a > pseudo-random number generator) from a perfectly well-defined model? For > example, I can easily generate simple linear models contaminated with > outliers that are quite difficult to fit (e.g. via resistant fitting > methods). In nonlinear fitting, it is quite easy to generate data from > oevrparameterized models that are quite difficult to fit or whose fit is > very sensitive to initial conditions. Remember: the design (for the > covariates) at which you fit the data must support the parameterization. > > The most dramatic examples are probably of simple nonlinear model systems > with no noise which produce chaotic results when parameters are in certain > ranges. These would be totally impossible to recover from the "data." > > So I repeat: just because you can generate data from a simple model, why > should it be easy to fit the data and recover the model? > > Cheers, > > Bert Gunter > Genentech > > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html