Try: sum(lm.fit(x, y)$residuals^2)
On Mon, Sep 8, 2008 at 12:52 PM, Dimitri Liakhovitski <[EMAIL PROTECTED]> wrote: > 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 > <[EMAIL PROTECTED]> 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 <[EMAIL PROTECTED]> >> 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. >>> [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. >>> >> > > > > -- > 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.