On Jul 21, 2011, at 1:04 AM, Daniel Malter wrote:
http://mlg.eng.cam.ac.uk/dave/rmbenchmark.php
I haven't ever tried it myself, but online sources suggest that
Matlab possibly gains speed by internally avoiding loops rather than
looping faster. What would stand at the end if this were true,
however, is improved end user speed.
When I ran the Toeplitz matrix creation test on a 3 year-old Mac, not
the fastest available at the time, inside their 20 run test with the
outer() function I get:
---------
b <- outer(j, k, function(j,k) abs(j - k) + 1)
Creation of a 220x220 Toeplitz matrix (loops)_______ (sec): 0.0034
-------------
When I run their code I get a number very similar to theirs:
-------
for (j in 1:220) {
for (k in 1:220) {
b[k,j] <- abs(j - k) + 1
}
}
Creation of a 220x220 Toeplitz matrix (loops)_______ (sec): 0.2338
-----------
So I guess that suggests that either the loop construct or the 220 x
220 assignments are the holdup since the calculation and single
assignment don't take much time.
I was thinking you were comparing loops to *apply strategies, but I
guess your comparison was different.
--
David.
Daniel
________________________________________
From: David Winsemius [dwinsem...@comcast.net]
Sent: Wednesday, July 20, 2011 9:01 AM
To: Daniel Malter
Cc: r-help@r-project.org
Subject: Re: [R] loops and simulation
On Jul 20, 2011, at 1:34 AM, Daniel Malter wrote:
snipped
requests, except that you were referring to SAS and had heard that R
"does
not like loops." (This is factually wrong. But R can be slow
looping).
Where did you hear this? Can you cites any references?
--
David Winsemius, MD
West Hartford, CT
David Winsemius, MD
West Hartford, CT
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