[R] optimisation procedure with flat log-likelihood

[Camarda, Carlo Giovanni]

Dear R-friends,
I use

optim(par=c(mystartingpoints), fn=myloglikelihoodfunction, gr=NULL,
                    method=c("L-BFGS-B"),  ## I would like to do not use any
bounds
                    control=list(trace=6, ## just to see what it's going on
                                 maxit=c(20000)), ## to be sure the it
doesn't stop reaching the max iterations
                    data=mydataset)

to optimize some demographic model. I assume that the log-likelihood is
relatively flat because the estimated results are very similar to my
starting values. In addition, I know the "real" parameters as I have used
simulated data (which have been also found by using GAUSS and replicated by
it).
I already tried various methods and also various starting values but it did
not help. Can maybe anyone give me some suggestion what I could do?

Thanks,
Carlo Giovanni Camarda



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