On Mar 26, 2011, at 10:26 PM, fisken wrote:
I was wondering if it is possible to do the following in a smarter
way.
I want get the mean value across the columns of a matrix, but I want
to do this on subrows of the matrix, given by some vector(same length
as the the number of rows). Something like
nObs<- 6
nDim <- 4
m <- matrix(rnorm(nObs*nDim),ncol=nDim)
fac<-sample(1:(nObs/2),nObs,rep=T)
##loop trough different 'factor' levels
for (i in unique(fac))
print(apply(m[fac==i,],2,mean))
This would be a lot simpler and faster:
colMeans(m[unique(fac),])
#[1] 1.3595197 -0.1374411 0.1062527 -0.3897732
Now, the problem is that if a value in 'fac' only occurs once, the
'apply' function will complain.
Because "[" will drop single dimensions and so the matrix becomes a
vector and looses the number-2 margin. Use drop=FALSE to prevent this,
and note the extra comma:
print(apply(m[1, , drop=FALSE],2,mean))
--
David Winsemius, MD
West Hartford, CT
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