Dear list, I have an optimization problem that I would like to solve by Maximum Likelihood. I have analytical functions for the first and second derivatives of my parameters. In addition, some parameters are constrained between 0 and 1, while some others can vary freely between -Inf and +Inf.
I am looking for an optimization function to solve this problem. I understand that the base optim function doesn't take a Hessian function, it only computes it numerically. I found the maxLik package that takes the function as a "hess" parameter but the maxNR method (the only one that uses the Hessian function) can't be bounded. Surprisingly I couldn't find a function doing both. Any suggestions for a function doing bounded optimization with an analytical Hessian function? Thanks, Xavier ______________________________________________ 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.
