how to rewrite this without a loop ?

Dear Rexperts,

First of all let me say that R is a wonderful and useful piece of software.

The only thing is that sometimes it takes me a long time to find out how 
something can be done, especially when aiming to write compact (and 
efficient) code.

For instance, I have the following function (very rudimentary) which 
takes a (very specific) data frame as input and for certain subsets
calculates the rank correlation between two corresponding columns.
The aim is to add all the rank correlations.

<code>
add.fun <- function(perf.data) {
   ss <- 0
   for (i in 0:29) {
       ss <- ss + cor(subset(perf.data, dataset == i)[3], 
subset(perf.data, dataset == i)[7], method = "kendall")
   }
   ss   
}
</code>

As one can see this function uses a for-loop.  Now chapter 9 of 'An 
introduction to R' tells us that we should avoid for-loops as much as 
possible.

Is there an obvious way to avoid this for-loop is this case ?

I would like to see something in the lines of

(maple style)

<code>
add( seq(FUN(i), i = 0..29) )
</code>

Greetings

Stijn.

<code>
add.fun <- function(perf.data) {
  ss <- 0
  for (i in 0:29) {
  	ss <- ss + cor(subset(perf.data, dataset == i)[3], subset(perf.data, 
dataset == i)[7], method = "kendall")
  }
  ss	}
</code>

As one can see this function uses a for-loop.  Now chapter 9 of 'An 
introduction to R' tells us that we should avoid for-loops as much as 
possible.

On Thu, 18 Nov 2004, Stijn Lievens wrote:

<code>
add.fun <- function(perf.data) {
  ss <- 0
  for (i in 0:29) {
      ss <- ss + cor(subset(perf.data, dataset == i)[3], 
subset(perf.data, dataset == i)[7], method = "kendall")
  }
  ss    }
</code>

As one can see this function uses a for-loop.  Now chapter 9 of 'An 
introduction to R' tells us that we should avoid for-loops as much as 
possible.

You don't say whether `dataset' is the name of a column in `perf.data'. 
Assuming it is, and assuming that 0:29 are all the values of `dataset'

sum(by(perf.data, list(perf.data$dataset),
          function(d)  cor(d[,3],d[,7], method="kendall")))

would work.  

If this is faster it will be because you don't call 
subset() twice per iteration, rather than because you are avoiding a 
loop.  However it has other benefits: it doesn't have the variable `i', 
it doesn't have to change the value of `ss', and it doesn't have the 
range of `dataset' hard-coded into it.  These are all clarity 
optimisations.

    -thomas