try this:
A <- matrix(rnorm(10*4), 10, 4)
B <- matrix(rnorm(3*4), 3, 4)
C <- matrix(rnorm(5*4), 5, 4)
nrA <- nrow(A); nrB <- nrow(B); nrC <- nrow(C)
ind <- as.matrix(expand.grid(1:nrA, 1:nrB, 1:nrC))
D <- rowSums(A[ind[, 1], ] * B[ind[, 2], ] * C[ind[, 3], ])
dim(D) <- c(nrA, nrB, nrC)
D
I hope it helps.
Best,
Dimitris
----
Dimitris Rizopoulos
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
http://www.student.kuleuven.be/~m0390867/dimitris.htm
----- Original Message -----
From: "Giuseppe Paleologo" <[EMAIL PROTECTED]>
To: <r-help@r-project.org>
Sent: Thursday, May 08, 2008 11:20 PM
Subject: [R] speeding up a special product of three arrays
I am struggling with R code optimization, a recurrent topic on this
list.
I have three arrays, say A, B and C, all having the same number of
columns.
I need to compute an array D whose generic element is
D[i, j, k] <- sum_n A[i, n]*B[j, n]*C[k, n]
Cycling over the three indices and subsetting the columns won't do.
Is there
any way to implement this efficiently in R or should I resign to do
this in
C?
Thanks,
Giuseppe
[[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.
Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm
______________________________________________
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.
