[R] Question about multiple regression

Dimitri Liakhovitski ld7631 at gmail.com
Mon Sep 8 18:56:02 CEST 2008

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
<ripley at stats.ox.ac.uk> 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.
>> Dimitri.Liakhovitski at markettools.com
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> --
> 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

Dimitri Liakhovitski
MarketTools, Inc.
Dimitri.Liakhovitski at markettools.com

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