problem of convergence of simulated data

I've faced the same problem with fitting models before.  I'm simulating 
different permutations of data sets, starting off with the baseline that 
has almost no variance at all, hence it is difficult for the algorithm 
to converge.  Having said that, the estimates will be more than adequate 
if I could relax the convergence criteria even a little.  Is there a way 
to do such with the lme procedure?

Thanks for any suggestions.

J


Error in lme.formula(nmalor ~ 0 + nmatr1 + nmatr3, ~1 | trtpair, data = 
fednmadat,  :
   nlminb problem, convergence error code = 1
   message = singular convergence (7)

Dr. Jim Maas
University of East Anglia