Ok. I have the following likelihood function. L <- p*dpois(x,a)*dpois(y,b+c)+(1-p)*dpois(x,a+c)*dpois(y,b)
where I have 100 points of (x,y) and parameters c(a,b,c,p) to estimate. Constraints are: 0 < p < 1 a,b,c > 0 c < a c < b I construct a loglikelihood function out of this. First ignoring the last two constraints, it takes optim with box constraint about 1-2 min to estimate this. I have to estimate the MLE on about 200 rolling windows. This will take very long. Is there any faster implementation? Secondly, I cannot incorporate the last two contraints using optim function. Thank you, rc On Thu, Oct 29, 2009 at 9:02 PM, Ravi Varadhan <rvarad...@jhmi.edu> wrote: > > You have hardly given us any information for us to be able to help you. Give > us more information on your problem, and, if possible, a minimal, > self-contained example of what you are trying to do. > > Ravi. > ____________________________________________________________________ > > Ravi Varadhan, Ph.D. > Assistant Professor, > Division of Geriatric Medicine and Gerontology > School of Medicine > Johns Hopkins University > > Ph. (410) 502-2619 > email: rvarad...@jhmi.edu > > > ----- Original Message ----- > From: R_help Help <rhelp...@gmail.com> > Date: Thursday, October 29, 2009 8:24 pm > Subject: [R] Fast optimizer > To: r-help@r-project.org, r-sig-fina...@stat.math.ethz.ch > > >> Hi, >> >> I'm using optim with box constraints to MLE on about 100 data points. >> It goes quite slow even on 4GB machine. I'm wondering if R has any >> faster implementation? Also, if I'd like to impose >> equality/nonequality constraints on parameters, which package I should >> use? Any help would be appreciated. Thank you. >> >> rc >> >> ______________________________________________ >> R-help@r-project.org mailing list >> >> PLEASE do read the posting guide >> and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ 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.