On 02-03-2012, at 16:12, Diogo Alagador wrote: > Dear all, > > Sorry to insist in this, but I am passing really "bad times" trying to solve > the problem. Just to remember you: > > I am tryng to solve a nonlinear optimization probel using the solnp function. > I have different datasets. For the smaller I get full solutions, for > the bigger I got an error message stating: > > ######################################## > Iter: 1 fn: 101.8017 Pars: 0.21000 0.21000 0.21000 0.21000 > 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 > 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 > 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 > 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 > 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 > 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 > 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 0.21000 > 0.21000 0.21000 0.21000 0.21000 > > solnp--> Solution not reliable....Problem Inverting Hessian. > Warning messages: > 1: In p0 * vscale[(neq + 2):(nc + np + 1)] : > longer object length is not a multiple of shorter object length > 2: In cbind(temp, funv) : > number of rows of result is not a multiple of vector length (arg > 1) ######################################## > > > Anyone knows what may be the reason? Just remembering that the same > problem runs OK for smaller datasets.
No. You have not provided enough information. I know nothing about solnp but I am quite prepared to investigate. But from the warning message I would guess that [(neq + 2):(nc + np + 1)] is simply incorrect in your specific case. But no data or no description of your data, no function, no reproducible example ===> No help. You should really try to be more informative. Berend ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
