If "any idea of a for loop is disastrous," why are you using apply,
which is basically a for loop?
I think you have framed the question in such a way that loops are
inevitable. You are already using the LHS as a matrix, which is the
main speedup I could think of. However, you can avoid some subscripting
and use colMeans for a bit of speedup.
# fake data... you didn't provide any
A <- data.frame( a=1:10, b=(0:9)*2 )
B <- data.frame( c=A$a+rnorm(10), d=A$b+rnorm(10), e=A$a+A$b+rnorm(10)
)
A <- as.matrix(A)
B <- as.matrix(B)
linRegUtility2 <- function(x,y){
regRes <- lm(y~x)[["residuals"]]
( regRes[ nrow( regRes ), ] - colMeans( regRes ) )/ apply( regRes,
2, sd )
}
C <- apply( A, 2, linRegUtility2, y=B )
However, this is only getting about 9% improvement on my computer.
Stathis Metsovitis <stmet...@gmail.com> wrote:
Hi all,
I am trying to perform some analysis on the residuals of pair-wise
linear
regressions between two large sets A with dimensions {k x m}, and B {k
x n}
. So I need to regress every column B[,j] of B on every column A[,i]
of
A
and produce a matrix C with dimensions {m x n}, so that C[i,j]
contains
the
z-score of the k-th (last) residual of the aforementioned linear
regression.
I have tried the following code, but i don't seem to get it work.
Moreover,
any idea of using a for loop is disastrous since A and B are very
large
matrices. I'd be grateful for any suggestions!
C <- apply( A[ ,1:dim(A)[2] ], 2, linRegZscore, y=A[ ,1:dim(A)[2]] )
where linRegZscore is the following function
linRegUtility1 <- function(x,y){
regRes <- lm(y~x)$residuals
( regRes[dim(regRes)[1]]-apply(regRes, 2, mean) )/( apply(regRes,2,
sd)
)
}
[[alternative HTML version deleted]]
______________________________________________
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.
