problem of convergence of simulated data
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On 06/27/2011 10:10 AM, Jim Maas wrote:
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)
You could play with the "tolerance" and "msTol" parameters (see ?lmeControl), although I don't know if that will actually help. Alternately, try try() if you're willing to filter out failures. Ben Bolker -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.10 (GNU/Linux) Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org/ iEYEARECAAYFAk4Ij+4ACgkQc5UpGjwzenOh6QCePP6ssyl9kSeEBX26Mwrb+aXO HggAniwM0LGMhATOF5kVJo40F/Lky0EB =8a+0 -----END PGP SIGNATURE-----