How can I avoid nested 'for' loops or quicken the process?

Thankyou for the clarification, Brian. This is very helpful (as usual).

However, I think the important point, which I misstated, is that whether it
be for() or, e.g. lapply(), the "loop" contents must be evaluated at the
interpreted R level, and this is where most time is typically spent. To get
the speedup that most people hope for, avoiding the loop altogether (i.e.
moving loop **and** evaluations) to C level, via R programming -- e.g. via
use of matrix operations, indexing, or built-in .Internal functions, etc. --
is the key.

Please correct me if I'm (even partially) wrong. As you know, the issue
arises frequently.

-- Bert Gunter
Genentech

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
Behalf Of Prof Brian Ripley
Sent: Friday, December 26, 2008 12:44 AM
To: Oliver Bandel
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] How can I avoid nested 'for' loops or quicken the process?

Bert Gunter <gunter.berton <at> gene.com> writes:

FWIW:

Good advice below! -- after all, the first rule of optimizing code is:
Don't!

For the record (yet again), the apply() family of functions (and their
packaged derivatives, of course) are "merely" vary carefully written

for()

loops: their main advantage is in code readability, not in efficiency

gains,

which may well be small or nonexistent. True efficiency gains require
"vectorization", which essentially moves the for() loops from interpreted
code to (underlying) C code (on the underlying data structures): e.g.
compare rowMeans() [vectorized] with ave() or apply(..,1,mean).

[...]

The apply-functions do bring speed-advantages.

This is not only what I read about it,
I have used the apply-functions and really got
results faster.

The reason is simple: an apply-function does
make in C, what otherwise would be done on the level of R
with for-loops.

Not true of apply(): true of lapply() and hence sapply().  I'll leave you 
to check eapply, mapply, rapply, tapply.

So the issue is what is meant by 'the apply() family of functions': people 
often mean *apply(), of which apply() is an unusual member, if one at all.

[Historical note: a decade ago lapply was internally a for() loop.  I 
rewrote it in C in 2000: I also moved apply to C at the same time but it 
proved too little an advantage and was reverted.  The speed of lapply 
comes mainly from reduced memory allocation: for() is also written in C.]

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 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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