Does this do what you want?
m1 <- cbind(1:5,1:5,1:5)
m2 <- m1
for(i in 2:ncol(m1)){
m2[,i] <- apply(m1[,1:i],1,sum)
}
m2
ut <- diag( ncol(m1) )
ut[upper.tri(ut)] <- 1
m3 <- m1 %*% ut
m3
all.equal(m2,m3)
hope this helps,
--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.s...@imail.org
801.408.8111
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
> project.org] On Behalf Of Eleni Rapsomaniki
> Sent: Wednesday, April 14, 2010 6:18 AM
> To: r-help@r-project.org
> Subject: [R] Running cumulative sums in matrices
>
>
> Dear R-helpers,
>
> I have a huge data-set so need to avoid for loops as much as possible.
> Can someone think how I can compute the result in the following example
> (that uses a for-loop) using some version of apply instead (or any
> other similarly super-efficient function)?
>
> example:
> #Suppose a matrix:
> m1=cbind(1:5,1:5,1:5)
>
> #The aim is to create a new matrix with every column containing the
> cumulative sum of all previous columns.
> m2=m1
> for(i in 2:ncol(m1)){
> m2[,i]=apply(m1[,1:i],1,sum)
> }
> m2
>
> Many thanks in advance
>
> Eleni Rapsomaniki
>
> Research Associate
> Strangeways Research Laboratory
> Department of Public Health and Primary Care
> University of Cambridge
>
>
> ______________________________________________
> 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.
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