-----Original Message-----
From: Prof Brian Ripley [mailto:ripley@stats.ox.ac.uk]
Sent: 05 August 2003 09:50
To: Marsland, John
Cc: r-devel@stat.math.ethz.ch
Subject: RE: [Rd] RE: [R] ^ operation much slower in R 1.7.1 than in R
1.7 .0 ???
So that pretty conclusively nails this as a compiler/runtime
difference.
Which versions of the compiler and mingw-runtime did you use?
We'll need to wait until Duncan M returns to find out what he used.
On Tue, 5 Aug 2003, Marsland, John wrote:
I have both the CRAN binary and my own compiled version of
same machine (Dell Pentium III 800 MHz running NT 4)
Using the example provided earlier:
phi <- 1.6180339887498949
a <- floor(runif(750000)*1000)
system.time(b <- (phi^a - (-phi)^(-a))/sqrt(5))[3]
I get 10.99 secs on the CRAN binary and 2.09 secs on my own compiled
version.
I hope this helps someone ...
Regards,
John Marsland
-----Original Message-----
From: Prof Brian D Ripley [mailto:ripley@stats.ox.ac.uk]
Sent: 05 August 2003 09:03
To: Philippe Grosjean
Cc: r-devel@stat.math.ethz.ch
Subject: [Rd] RE: [R] ^ operation much slower in R 1.7.1 than
in R 1.7.0
???
On Tue, 5 Aug 2003, Philippe Grosjean wrote:
I propose to move this thread to R-devel...
Prof. Brian Ripley wrote:
And are you able to give an explanation? For example, did
each under the same compiler system?
I just noticed that behaviour yesterday, and had not much
investigate it. I compiled 1.7.0 myself (but compared with
provided on CRAN; no changes). I used the 1.7.1 binary
know these binaries are not supported, so we (Windows
look at that by ourselve. Indeed yes, I'll first compile
compiler I used for 1.7.0.
I doubt if this is worth R-core's time to pursue, so over
users to find an explanation and fix.
OK. But I was wondering if people at R-core team,
worked on Windows specific aspects, would have in mind some
between 1.7.0 and 1.7.1 than can cause this. Since these
corrections of bugs, the list is hopefully not so long...
a lot to have these hints. Thanks very much.
No idea from me, and the effect is not seen on other platforms.
--
Brian D. Ripley, ripley@stats.ox.ac.uk
Professor of Applied Statistics,