I won't requote all the other msgs, but the latest (and possibly a bit glitchy) version of optimx on R-forge
1) finds that some methods wander into domains where the user function fails try() (new optimx runs try() around all function calls). This includes L-BFGS-B 2) reports that the scaling is such that you really might not expect to get a good solution then 3) Actually gets a better result than the > xlf<-myfunc(c(0.888452533990788,94812732.0897449)) > xlf [1] 334.607 > with Kelley's variant of Nelder Mead (from dfoptim package), with > myoptx method par fvalues fns grs itns conv KKT1 4 LBFGSB NA, NA 8.988466e+307 NA NULL NULL 9999 NA 2 Rvmmin 0.1, 200186870.6 25593.83 20 1 NULL 0 FALSE 3 bobyqa 6.987875e-01, 2.001869e+08 1933.229 44 NA NULL 0 FALSE 1 nmkb 8.897590e-01, 9.470163e+07 334.1901 204 NA NULL 0 FALSE KKT2 xtimes meths 4 NA 0.01 LBFGSB 2 FALSE 0.11 Rvmmin 3 FALSE 0.24 bobyqa 1 FALSE 1.08 nmkb But do note the terrible scaling. Hardly surprising that this function does not work. I'll have to delve deeper to see what the scaling setup should be because of the nature of the function setup involving some of the data. (optimx includes parscale on all methods). However, original poster DID include code, so it was easy to do a quick check. Good for him. JN > ## Comparing this solution to Excel Solver solution: > myfunc(c(0.888452533990788,94812732.0897449)) > > -- Dimitri Liakhovitski marketfusionanalytics.com ______________________________________________ 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.
