Is sens really what you want? The denominator is the indexes,
e.g. if a row in goldstandard were c(0, 0, 1, 1) then you would
be dividing by 3+4. Also test[which(gold == 1)] is the same
as test[gold == 1] which is the same test * gold since gold
has only 0 and 1's in it. Perhaps what you really intend is to
take the average over those elements in each row of the first matrix
which correspond to 1's in the second in the corresponding
row of the second. In that case its just:
rowSums(newtest * goldstandard) / rowSums(goldstandard)
On 8/9/07, Johannes Hüsing <[EMAIL PROTECTED]> wrote:
> Dear ExpRts,
> I would like to perform a function with two arguments
> over the rows of two matrices. There are a couple of
> *applys (including mApply in Hmisc) but I haven't found
> out how to do it straightforward.
>
> Applying to row indices works, but looks like a poor hack
> to me:
>
> sens <- function(test, gold) {
> if (any(gold==1)) {
> sum(test[which(gold==1)]/sum(which(gold==1)))
> } else NA
> }
>
> numtest <- 6
> numsubj <- 20
>
> newtest <- array(rbinom(numtest*numsubj, 1, .5),
> dim=c(numsubj, numtest))
> goldstandard <- array(rbinom(numtest*numsubj, 1, .5),
> dim=c(numsubj, numtest))
>
> t(sapply(1:nrow(newtest), function(i) {
> sens(newtest[i,], goldstandard[i,])}))
>
> Is there any shortcut to sapply over the indices?
>
> Best wishes
>
>
> Johannes
>
> ______________________________________________
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