[R] Question about multiple regression
Prof Brian Ripley
ripley at stats.ox.ac.uk
Mon Sep 8 18:51:59 CEST 2008
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.
> Dimitri.Liakhovitski at markettools.com
> R-help at r-project.org mailing list
> 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, ripley at stats.ox.ac.uk
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
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