Hi,
I want to have a vignette in one of my R packages. Hence, I added an Sweave
file into the /inst/doc subdirectory of this package. Unfortunately, 'R CMD
check' gives a warning:
==
[...]
* checking tests ... OK
* checking package vignettes in
Guys,
Is anyone using snowfall? It seems that the last version is broken. sfinit
contains test code:
data(config, package = snowfall)
configM - as.matrix(t(config))
config - as.list(configM)
names(config) - dimnames(configM)[[2]]
.sfOption$SERVER -
Hello Arne,
I do not know if this matters, but have you used 'results = verbatim' in your R
code chunk? See page 13 in:
http://www.statistik.lmu.de/~leisch/Sweave/Sweave-manual.pdf
Best,
Bernhard
Hi,
I want to have a vignette in one of my R packages. Hence, I
added an Sweave
file into the
Hi Kurt,
I have committed your patch and your new spss_long.sav
example file, tested things and uploaded a new version of
'foreign', namely 0.8-27 to CRAN.
I vaguely remember that other useRs have asked for long-label
support in the past, so if you are (or know of) such a user,
we'd be glad if
Hi Bernhard!
On Wednesday 16 July 2008 14:16:05, you wrote:
I do not know if this matters, but have you used 'results = verbatim' in
your R code chunk? See page 13 in:
http://www.statistik.lmu.de/~leisch/Sweave/Sweave-manual.pdf
Thank you for this hint. I have tried this option, but it seems
The only way to overcome the problem I can find is to tweak the
R_CStackLimit with:
R_CStackLimit = (uintptr_t) -1;
The question I am having now is: what are the implications of doing
so, that is what are the potential problems ?
The R-extensions manual says:
Stack-checking can be disabled by
Laurent,
On Jul 16, 2008, at 9:02 AM, Laurent Gautier wrote:
The only way to overcome the problem I can find is to tweak the
R_CStackLimit with:
R_CStackLimit = (uintptr_t) -1;
The question I am having now is: what are the implications of doing
so, that is what are the potential problems ?
Guys,
I'm running R on both Windows Linux. I'm looking at a number of packages
for parallel execution. It seems that the most used packages are snow and
Rmpi.
snow seems more user friendly, but it doesn't run on windows. I see from
searching the mailing list that I'm not the first one to try
[EMAIL PROTECTED] writes:
Guys,
I'm running R on both Windows Linux. I'm looking at a number of packages
for parallel execution. It seems that the most used packages are snow and
Rmpi.
snow seems more user friendly, but it doesn't run on windows. I see from
searching the mailing list
Hello,
we are using Rmpi and snow on windows. It is working very well.
We are using Windows Server 2003 and *MPICH2.
I probably will manage to have some tests with the new snow
(*snow_0.3-3)* version this week.
Best
Markus
Martin Morgan schrieb:
[EMAIL PROTECTED] writes:
Guys,
I'm
Laurent Gautier wrote on 07/16/2008 08:02 AM:
The only way to overcome the problem I can find is to tweak the
R_CStackLimit with:
R_CStackLimit = (uintptr_t) -1;
The question I am having now is: what are the implications of doing
so, that is what are the potential problems ?
The problem is a
Markus,
That's interesting. I'm using snow_0.3-0 that's the version on CRAN. I see
that on the maintainer's website newer versions are available...
I just tried snow_0.3-3 and as you said it actually works fine!
Thanks a lot for the help, that's exactly what I was looking for!
// Giuseppe
McGehee, Robert writes:
Hello,
I wanted to suggest that the below method for split.Date be added to the
base library to significantly speed up splits with values of class Date.
In the below example I show a speed improvement of 175x for 1000 data
points. On a vector of size 1e6, the time
On Wed, 16 Jul 2008 14:57:39 +0200,
Arne Henningsen (AH) wrote:
Hi Bernhard!
On Wednesday 16 July 2008 14:16:05, you wrote:
I do not know if this matters, but have you used 'results = verbatim' in
your R code chunk? See page 13 in:
2008/7/16 Jeffrey Horner [EMAIL PROTECTED]:
Laurent Gautier wrote on 07/16/2008 08:02 AM:
The only way to overcome the problem I can find is to tweak the
R_CStackLimit with:
R_CStackLimit = (uintptr_t) -1;
The question I am having now is: what are the implications of doing
so, that is
Hi,
Wouldn't that make sense to have rowSums()/colSums() to preserve the
storage mode?
m - matrix(1:15, nrow=5)
storage.mode(m)
[1] integer
storage.mode(sum(m))
[1] integer
storage.mode(rowSums(m))
[1] double --- surprising!
Cheers,
H.
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