to the
Venables and Ripley S programming book.
On 26.06.2015 14:09, Stephen Milborrow wrote:
Once we have built a regression model, we typically want to use the
model for further processing, such as making predictions from the model
or plotting the residuals. Unfortunately, for many packages on CRAN
To avoid the NOTEs (which often triggers a 'pls fix' upon submission to
CRAN), I simply copied/pasted these functions to my package, but this
seems wasteful.
An issue is how one acknowledges the author of the cut and pasted code.
Assume that for one reason or another the original function
of incompatiblities
between R math and IEEE 754, if people think time spent doing that is worth
it.
Steve
www.milbo.users.sonic.net
- Original Message -
From: John Chambers [EMAIL PROTECTED]
To: Stephen Milborrow [EMAIL PROTECTED]
Cc: r-devel@r-project.org
Sent: Saturday, October 25, 2008 7
In R, 0 ^ NaN yields Inf. I would have expected NaN or perhaps 0. Is this
behaviour intended?
sessionInfo()
R version 2.8.0 (2008-10-20)
i386-pc-mingw32
locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
States.1252;LC_MONETARY=English_United
# code is shown above, 7 secs with standard R 2.6.2
Stephen Milborrow
www.milbo.users.sonic.net
# cm-post.R: compare solutions to the following post to
#r-devel from carlos martinez 12 apr 2008:
# Looking for a simple, effective a minimum execution time solution.
# For a vector as:
# c
There is a new version of the just-in-time compiler for R at
www.milbo.users.sonic.net/ra/index.html
With just-in-time compilation enabled, the convolution example from the
Extending R manual now runs about 30 times faster. The web page has more
information.
Stephen Milborrow
I'm not sure if this is connected but in R2.6.1 do_proctime is missing some
PROTECTs. The current code is
SEXP ans = allocVector(REALSXP, 5), nm = allocVector(STRSXP, 5);
and should be
SEXP ans, nm;
PROTECT(ans = allocVector(REALSXP, 5));
PROTECT(nm = allocVector(STRSXP, 5));
A
] + a[i] * b[j]
The loop will run about 30% faster. That's not much of a speedup, but the
code is still in early development and the figure will get much better.
If you are interested there is more information at
www.milbo.users.sonic.net/ra.
Stephen Milborrow
www.milbo.users.sonic.net
Greetings R developers,
R will run a little faster when executing pure R code if the function
R_CheckStack() is modified.
With the modification, the following code for example runs 15% faster
(compared to a virgin R-2.5.1 on my Windows XP machine):
N = 1e7
foo - function(x)
{
