Fast optimizer
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 <rvaradhan at 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: rvaradhan at jhmi.edu ----- Original Message ----- From: R_help Help <rhelpacc at gmail.com> Date: Thursday, October 29, 2009 8:24 pm Subject: [R] Fast optimizer To: r-help at r-project.org, r-sig-finance at 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 at r-project.org mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code.