On Thu, Feb 19, 2009 at 8:30 AM, Esmail Bonakdarian <esmail...@gmail.com> wrote: > Hi Kenn, > > Thanks for the suggestions, I'll have to see if I can figure out how to > convert the relatively simple call to lm with an equation and the data file > to the functions you mention (or if that's even feasible).
X <- model.matrix(formula, data) will calculate the X matrix for you. > > Not an expert in statistics myself, I am mostly concentrating on the > programming aspects of R. Problem is that I suspect my colleagues who > are providing some guidance with the stats end are not quite experts > themselves, and certainly new to R. > > Cheers, > > Esmail > > Kenn Konstabel wrote: >> >> lm does lots of computations, some of which you may never need. If speed >> really matters, you might want to compute only those things you will really >> use. If you only need coefficients, then using %*%, solve and crossprod will >> be remarkably faster than lm >> >> # repeating someone else's example >> # lm(DAX~., EuStockMarkets) >> >> y <- EuStockMarkets[,"DAX"] >> x <- EuStockMarkets >> x[,1]<-1 >> colnames(x)[1] <- "Intercept" >> >> lm(y ~ x-1) >> solve(crossprod(x), t(x))%*%y # probably this can be done more >> efficiently >> >> # and a naive timing >> >> > system.time( for(i in 1:1000) lm(y ~ x-1)) >> user system elapsed >> 14.64 0.33 32.69 >> > system.time(for(i in 1:1000) solve(crossprod(x), crossprod(x,y)) ) >> user system elapsed >> 0.36 0.00 0.36 >> >> >> Also lsfit() is a bit quicker than lm or lm.fit. >> >> Regards, >> Kenn > > ______________________________________________ > 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.
