If your problem is small enough just use a grid of starting values and run your optimization on each one and then take the best.
On 3/6/07, Dae-Jin Lee <[EMAIL PROTECTED]> wrote: > Hi all ! > > I've been trying to maximize a likelihood using optim( ) function, but it > seems that the function has several local maxima. I've tried in my algorithm > with different starting values and depending on them "optim" obtains > different results... > > I use the "L-BFGS-B" method setting the lower values as 1e-06, because my > parameters must be strictly positive. Also tried a log() transformation to > ensure that my parameters are positive. Don't know if this is useful in this > case... (also with notLog and notExp functions of mgcv package) > > the function nlminb( ) also have the same problems. > > > ¿Is there any thing I'm not considering? I mean other methods instead of > "L-BFGS-B"? > > How can I do to take a strategy to begin with "good" starting values? > > > Thanks in advance > > Dae-Jin > > PS: I'm trying to fit a mixed model with REML and several random effects, so > I maximize over several parameters... > > [[alternative HTML version deleted]] > > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > > ______________________________________________ R-help@stat.math.ethz.ch 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.
