yes Ben, this works indeed! Thanks a million!! On Mon, Mar 9, 2015 at 7:17 PM, Ben Bolker <bbol...@gmail.com> wrote:
> Sophia Kyriakou <sophia.kyriakou17 <at> gmail.com> writes: > > > > > hello, I am using the optim function to maximize the log likelihood of a > > generalized linear mixed model and I am trying to replicate glmer's > > estimated components. If I set both the sample and subject size to > q=m=100 > > I replicate glmer's results for the random intercept model with > parameters > > beta=-1 and sigma^2=1. But if I change beta to 2 glmer works and optim > > gives me the error message "function cannot be evaluated at initial > > parameters". > > > > If anyone could please help? > > Thanks > > snip to make gmane happy. > > It looks like you're getting floating-point under/overflow. If you do > all the computations on the log scale first and then exponentiate, > it seems to work, i.e.: > > piYc_ir[i,] <- lchoose(m,Y[i]) + Y[i]*(z+beta) + > (-z^2/(2*exp(psi))) - > m*(log1p(exp(z+beta))) - 0.5*(log(2*pi)+psi) > piYc_ir[i,] <- exp(piYc_ir[i,]) > > follow-ups should probably go to r-sig-mixed-mod...@r-project.org > instead ... > > Ben Bolker > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
