R help - Aug 2002 - avoiding "for()" loops: a question?

I have read in several places that one should attempt to avoid for loops
whenever possible.  In this spirit, I was playing with some code that I have
written to improve its efficiency and elegance.

The following iteratively drops a column from a data frame and applies a
function to the reminaing columns.  I replaced this for loop:

for (y in 1:dim(x)[2])  my.function (x[,-y])

with this:

sapply(1:dim(x)[2], function(y) my.function (x[,-y] ))

in an attempt to aviod "for()".

However, using system.time() to compare performance of the two functions shows
no difference in performance over 30 trials with each function on a 500 X 24
matrix (any edge seems in favor of the for loop).  (Win 98,PIII,128M,R 1.5.1)

Is the issue with the way I used sapply?  Is there a better way to do this?
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On Fri, 2 Aug 2002,  Brett Magill wrote:
> I have read in several places that one should attempt to avoid for loops
> whenever possible.  In this spirit, I was playing with some code that I
have
> written to improve its efficiency and elegance.
It's much less true in (current) R than in some other S implementations.
(S-PLUS 3.0 to 3.3 in particular.)
> The following iteratively drops a column from a data frame and applies a
> function to the reminaing columns.  I replaced this for loop:
>
> for (y in 1:dim(x)[2])  my.function (x[,-y])
That doesn't actually do anything unless my.function has side effects
(very undesirable).
> with this:
>
> sapply(1:dim(x)[2], function(y) my.function (x[,-y] ))
That returns a result.
> in an attempt to aviod "for()".
>
> However, using system.time() to compare performance of the two functions
shows
> no difference in performance over 30 trials with each function on a 500 X
24
> matrix (any edge seems in favor of the for loop).  (Win 98,PIII,128M,R
1.5.1)
>
> Is the issue with the way I used sapply?  Is there a better way to do this?
See `S Programming' for some real examples in different S dialects,
including R from 1999.


-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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