Hi, Let me make the following points in response to your questions:
1. Your call to optim() with "L-BFGS-B" as the method is correct. Just make sure that your function "f" is defined as negative log-likelihood, since optim is by default a minimizer. The other option is to define log-likelihood as usual, but set control=list(fnscale=-1). 2. You can add derivative (or gradient to be more precise) by defining that function and then using the "gr" argument in optim. Specifying exact gradient almost always improves the convergence of the iterative schemes, especially for ill-conditioned problems (flat region around the local minima). So, if it is not too much trouble, and you are confident of your differentiation skills, you should do that. However, in most cases the approximate finite-difference gradient used by optim() should be good enough. 3. Regardless of whether it is easy to compute the exact gradient or not, it is generally a bad idea to maximize the likelihood that involves the product of a large number of very small numbers. It is almost always better to maximize the log-likelihood. Since the objective function is additive rather than multiplicative, it has better numerical conditioning. Ravi. ---------------------------------------------------------------------------- ------- Ravi Varadhan, Ph.D. Assistant Professor, The Center on Aging and Health Division of Geriatric Medicine and Gerontology Johns Hopkins University Ph: (410) 502-2619 Fax: (410) 614-9625 Email: [EMAIL PROTECTED] Webpage: http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html ---------------------------------------------------------------------------- -------- -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Gustave Lefou Sent: Wednesday, March 05, 2008 1:34 PM To: r-help@r-project.org Subject: [R] box-constrained Hello everybody, I have a question about box-constrained optimization. I've done some research and I found that optim could do that. Are there other ways in R ? Is the following correct if I have a function f of two parameters belonging for example to [0,1] and [0,Infinity] ? optim(par=param, fn=f, method="L-BFGS-B", lower=c(0,0), upper=c(1,Inf)) My other question is whether it is possible to add the derivatives of my function (like in nlm) and whether it is better to add them ? If there is no need to add the derivatives, then I guess I could wish to optimize the likelihood directly rather than to optimize the log-likelihood... Indeed one aspect of the log-likelihood is to make the derivatives tractable (in iid cases). Do you agree ? Thank you ! Gustave [[alternative HTML version deleted]] ______________________________________________ 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. ______________________________________________ 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.
