nlme problems

I meant fitting not maximising, it is a nonlinear mixed effects  
model, with both fixed and random effects. My assumption is that for  
the function I am using the approximation approach used in nlme is  
not quite close enough, and nothing much that I can do, except for  
looking at starting values. I was hoping that someone would have  
other suggestions, so I will keep attempting to understand the  
control parameters.  I can add an extra parameter to the model and  
obtain a worse fit.

Ken

Dieter Menne writes:

I'm maximising a reasonably complex function using nlme (version
3.1-65, have also tried 3.1-66) and am having trouble with fixed
parameter estimates slightly away from the maximum of the log
likelihood. I have profiled the log likelihood and it is a parabola
but with sum dips. Interestingly changing the parameterisation moves
the dips around slightly. Unfortunately the PNLS step is finding a
maximum at the dips rather than the mle. I have tried using starting
values for the fixed parameters without change. Any ideas ?

Ken,

you should not use nlme for "maximising a complex function",  
because it's a
rather specialized tool for mixed-model statistical analysis. Try  
to use optim
directly, which has quite a few methods to choose from, and one of  
them might
work for your problem.

Dieter