[R] very fast OLS regression?
Dimitris Rizopoulos
d.rizopoulos at erasmusmc.nl
Wed Mar 25 22:11:11 CET 2009
check the following options:
ols1 <- function (y, x) {
coef(lm(y ~ x - 1))
}
ols2 <- function (y, x) {
xy <- t(x)%*%y
xxi <- solve(t(x)%*%x)
b <- as.vector(xxi%*%xy)
b
}
ols3 <- function (y, x) {
XtX <- crossprod(x)
Xty <- crossprod(x, y)
solve(XtX, Xty)
}
ols4 <- function (y, x) {
lm.fit(x, y)$coefficients
}
# check timings
MC <- 500
N <- 10000
set.seed(0)
x <- matrix(rnorm(N*MC), N, MC)
y <- matrix(rnorm(N*MC), N, MC)
invisible({gc(); gc(); gc()})
system.time(for (mc in 1:MC) ols1(y[, mc], x[, mc]))
invisible({gc(); gc(); gc()})
system.time(for (mc in 1:MC) ols2(y[, mc], x[, mc]))
invisible({gc(); gc(); gc()})
system.time(for (mc in 1:MC) ols3(y[, mc], x[, mc]))
invisible({gc(); gc(); gc()})
system.time(for (mc in 1:MC) ols4(y[, mc], x[, mc, drop = FALSE]))
I hope it helps.
Best,
Dimitris
ivo welch wrote:
> Dear R experts:
>
> I just tried some simple test that told me that hand computing the OLS
> coefficients is about 3-10 times as fast as using the built-in lm()
> function. (code included below.) Most of the time, I do not care,
> because I like the convenience, and I presume some of the time goes
> into saving a lot of stuff that I may or may not need. But when I do
> want to learn the properties of an estimator whose input contains a
> regression, I do care about speed.
>
> What is the recommended fastest way to get regression coefficients in
> R? (Is Gentlemen's weighted-least-squares algorithm implemented in a
> low-level C form somewhere? that one was always lightning fast for
> me.)
>
> regards,
>
> /ivo
>
>
>
> bybuiltin = function( y, x ) coef(lm( y ~ x -1 ));
>
> byhand = function( y, x ) {
> xy<-t(x)%*%y;
> xxi<- solve(t(x)%*%x)
> b<-as.vector(xxi%*%xy)
> ## I will need these later, too:
> ## res<-y-as.vector(x%*%b)
> ## soa[i]<-b[2]
> ## sigmas[i]<-sd(res)
> b;
> }
>
>
> MC=500;
> N=10000;
>
>
> set.seed(0);
> x= matrix( rnorm(N*MC), nrow=N, ncol=MC );
> y= matrix( rnorm(N*MC), nrow=N, ncol=MC );
>
> ptm = proc.time()
> for (mc in 1:MC) byhand(y[,mc],x[,mc]);
> cat("By hand took ", proc.time()-ptm, "\n");
>
> ptm = proc.time()
> for (mc in 1:MC) bybuiltin(y[,mc],x[,mc]);
> cat("By built-in took ", proc.time()-ptm, "\n");
>
> ______________________________________________
> R-help at 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.
>
--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus University Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Tel: +31/(0)10/7043478
Fax: +31/(0)10/7043014
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