[EMAIL PROTECTED] wrote:
> Folks,
>
> I have a 3000 x 4 matrix (y), which I need to regress row-by-row against a
> 4-vector (x) to create a
> matrix lm.y of intercepts and slopes. To illustrate:
>
> y <- matrix(rnorm(12000), ncol = 4)
> x <- c(1/12, 3/12, 6/12, 1)
>
> system.time(lm.y <- t(apply(y, 1, function(z) lm(z ~ x)$coefficient)))
> [1] 44.72 18.00 69.52 NA NA
>
> Takes more than a minute to do (and I need to do many similar regressions
> a day).
>
> Is there a more efficient way of handling this?
>
> I'm running R 2.4.1 on Windows XP Service Pack 2 on a Intel Xeon dual-core
> 2.66GHz with 3GB RAM.
>
> Thanks very much,
>
> Murali
y <- matrix(rnorm(12000), ncol = 4)
x <- c(1/12, 3/12, 6/12, 1)
system.time(lm.y1 <- t(coef(lm(t(y) ~ x))))
user system elapsed
0.03 0.00 0.04
system.time(lm.y2 <- t(apply(y, 1, function(z) lm(z ~ x)$coefficient)))
user system elapsed
19.70 0.05 20.45
all.equal(lm.y1, lm.y2)
[1] TRUE
>
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