I meant the parscale parameter. On Sat, Nov 14, 2015 at 10:30 AM, Gabor Grothendieck <ggrothendi...@gmail.com> wrote: > Tyipcally the parameters being optimized should be the same order of > magnitude or else you can expect numerical problems. That is what the > fnscale control parameter is for. > > On Sat, Nov 14, 2015 at 10:15 AM, Lorenzo Isella > <lorenzo.ise...@gmail.com> wrote: >> Dear All, >> I am using optim() for a relatively simple task: a linear model where >> instead of minimizing the sum of the squared errors, I minimize the sum >> of the squared relative errors. >> However, I notice that the default algorithm is very sensitive to the >> choice of the initial fit parameters, whereas I get much more stable >> (and therefore better?) results with the BFGS algorithm. >> I would like to have some feedback on this (perhaps I made a mistake >> somewhere). >> I provide a small self-contained example. >> You can download a tiny data set from the link >> >> https://www.dropbox.com/s/tmbj3os4ev3d4y8/data-instability.csv?dl=0 >> >> whereas I paste the script I am using at the end of the email. >> Any feedback is really appreciated. >> Many thanks >> >> Lorenzo >> >> ################################################################ >> >> min.perc_error <- function(data, par) { >> with(data, sum(((par[1]*x1 + par[2]*x2+par[3]*x3 - >> y)/y)^2)) >> } >> >> par_ini1 <- c(.3,.1, 1e-3) >> >> par_ini2 <- c(1,1, 1) >> >> >> data <- read.csv("data-instability.csv") >> >> mm_def1 <-optim(par = par_ini1 >> , min.perc_error, data = data) >> >> mm_bfgs1 <-optim(par = par_ini1 >> , min.perc_error, data = data, method="BFGS") >> >> print("fit parameters with the default algorithms and the first seed >> ") >> print(mm_def1$par) >> >> print("fit parameters with the BFGS algorithms and the first seed ") >> print(mm_bfgs1$par) >> >> >> >> mm_def2 <-optim(par = par_ini2 >> , min.perc_error, data = data) >> >> mm_bfgs2 <-optim(par = par_ini2 >> , min.perc_error, data = data, method="BFGS") >> >> >> >> >> print("fit parameters with the default algorithms and the second seed >> ") >> print(mm_def2$par) >> >> print("fit parameters with the BFGS algorithms and the second seed ") >> print(mm_bfgs2$par) >> >> ______________________________________________ >> 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. > > > > -- > Statistics & Software Consulting > GKX Group, GKX Associates Inc. > tel: 1-877-GKX-GROUP > email: ggrothendieck at gmail.com
-- Statistics & Software Consulting GKX Group, GKX Associates Inc. tel: 1-877-GKX-GROUP email: ggrothendieck at gmail.com ______________________________________________ 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.