Disclaimer: I have **NO IDEA** of the details of what you want to do or why -- but I am willing to bet that there are better ways of doing it than 1.8 mm multiple refressions that take 270 secs each!! (which I find difficult to believe in itself -- are you sure you are doing things right? Something sounds very fishy here: R's regression code is typically very fast).
-- Bert Gunter -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Dimitri Liakhovitski Sent: Monday, September 08, 2008 9:56 AM To: Prof Brian Ripley Cc: R-Help List Subject: Re: [R] Question about multiple regression Yes, see my previous e-mail on how long R takes (270 seconds for one of the 1,800,000 sets I need) - using system.time. Not sure how to test the same for Fortran... On Mon, Sep 8, 2008 at 12:51 PM, Prof Brian Ripley <[EMAIL PROTECTED]> wrote: > Are you sure R's ways are not fast enough (there are many layers underneath > lm)? For an example of how you might do this at C/Fortran level, see the > function lqs() in MASS. > > On Mon, 8 Sep 2008, Dimitri Liakhovitski wrote: > >> Dear R-list, >> maybe some of you could point me in the right direction: >> >> Are you aware of any FREE Fortran or Java libraries/actual pieces of >> code that are VERY efficient (time-wise) in running the regular linear >> least-squares multiple regression? > > A lot of the effort is in getting the right answer fast, including for e.g. > collinear inputs. > >> More specifically, I have to run small regression models (between 1 >> and 15 predictors) on samples of up to N=700 but thousands and >> thousands of them. >> >> I am designing a simulation in R and running those regressions and R >> itself is way too slow. So, I am thinking of compiling the regression >> run itself in Fortran and Java and then calling it from R. > > I think Java is unlikely to be fast compared to the Fortran R itself uses. > > Have you profiled to find where the time is really being spent (both R and > C/Fortran profiling if necessary). > >> >> Thank you very much for any advice! >> >> Dimitri Liakhovitski >> MarketTools, Inc. >> [EMAIL PROTECTED] >> >> ______________________________________________ >> 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. >> > > -- > Brian D. Ripley, [EMAIL PROTECTED] > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > University of Oxford, Tel: +44 1865 272861 (self) > 1 South Parks Road, +44 1865 272866 (PA) > Oxford OX1 3TG, UK Fax: +44 1865 272595 > -- Dimitri Liakhovitski MarketTools, Inc. [EMAIL PROTECTED] ______________________________________________ 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.
