Hi all, Here is a summary of substantive replies to my posts (on both s-news and r-help) regarding use of Excel's Solver for a nonlinear regression problem. A number of people replied that Solver performs well as an optimizer based on experience, particularly if given reasonable starting values. A number of other people replied that it performs poorly based on experience. Whether or not it arrives at a bona fide solution, several people pointed out limitations to using Solver associated with lack of diagnostics and related statistical output. When using Solver, you cannot "trace the internals" of the solving process, and you cannot obtain the Hessian matrix or variance-covariance matrix. One user stated that he sometimes uses Excel's Solver to analyze the same problem he has previously done in S+ or R; if it arrives at the same answer, he's happy. I was also reminded of several general advantages of using a command line language (ease of debugging, portability to other problems or other users, etc.). Adding my own comment, that general issue applies to using Solver in that it is impossible (I think) to tell after the fact what options were selected for the optimization. The consensus was that someone in my shoes would do well to learn S+/R, or AD Model Builder ... but then you're all proficient in S+/R already :-) Thanks for your input, Kristian
Kristian Omland Postdoctoral Research Associate Vermont Cooperative Fish & Wildlife Research Unit Rubenstein School of Environment & Natural Resources University of Vermont Burlington VT 05405 voice: (802)656-2496 fax: (802)656-8683 web page: http://www.uvm.edu/~komland