[R] Question about multiple regression

[Dimitri Liakhovitski]

Thank you for reminding me, Gabor. I forgot to mention: So far, I have
run one test set of regressions using lm. It took R 270 sec. I need to
run 1,800,000 of those, which would imply 15.4 years of computing time
:)

I have not done the same for lm.fit because I am not sure how to get
model R squared from lm.fit.

Dimitri

On Mon, Sep 8, 2008 at 12:17 PM, Gabor Grothendieck
<ggrothendieck at gmail.com> wrote:
> I would test the speed before making such as assumption.  Note that
> lm.fit is faster than lm and if they have the same x matrix then
> you can do many in one call by having y be a matrix.
>
> On Mon, Sep 8, 2008 at 12:05 PM, Dimitri Liakhovitski <ld7631 at gmail.com> 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?
>> 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.
>>
>> Thank you very much for any advice!
>>
>> Dimitri Liakhovitski
>> MarketTools, Inc.
>> Dimitri.Liakhovitski at markettools.com
>>
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>> and provide commented, minimal, self-contained, reproducible code.
>>
>



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