On Thu, Mar 01, 2012 at 11:06:51AM -0600, Douglas Bates wrote:
> My purpose in mentioning the Julia language (julialang.org) here is
> not to start a flame war. I find it to be a very interesting
> development and others who read this list may want to read about it
> too.
[...]
Very interesting
Mario
I think of the RUnit and svUnit testing to be in addition to the
standard R package testing framework. You can get unit and more
integrated testing results, with the behaviour I think you are looking
for, simply by putting small test files in the tests/ directory of the
package. These
good day here,
I'm maintaining a couple of R modules, both on r-forge.
tests for these modules are written making use of unit testing, and I
make use of the svUnit module, part of SciViews-R.
I also make use of examples in the .Rd files.
my question regards 'R CMD check pkg'.
if an _example_ i
On Mar 2, 2012, at 8:57 AM, Ole Fredslund Christensen wrote:
> Dear R-devel
>
> Thought I better report this. An example is shown below.
>
>> vec <- rnorm(100)+10.5
>> ss <- summary(vec)
>> print(ss)
> Min. 1st Qu. MedianMean 3rd Qu.Max.
> 8.433 9.886 10.450 10.560 11.300 12.7
Dear R-devel
Thought I better report this. An example is shown below.
> vec <- rnorm(100)+10.5
> ss <- summary(vec)
> print(ss)
Min. 1st Qu. MedianMean 3rd Qu.Max.
8.433 9.886 10.450 10.560 11.300 12.720
> for(kk in 1:length(ss)) print(ss[[kk]])
[1] 8.433
[1] 9.886
[1] 10.45
[
Dear Uwe,
looking again my environment with configuration given, I missed some, sorry.
I downloaded the last version and compiled it with my updated
environment : make check is Ok.
Thank you very much for your quick help
Best regards,
Denis
On 02/03/12 14:44, Uwe Ligges wrote:
1. H
On Fri, Mar 02, 2012 at 01:36:34PM +0100, Karl Forner wrote:
> Thanks for your quick reply.
>
> About the rngSetSeed package: is it usable at c/c++ level ?
Not directly. The rngSetSeed package is meant to provide an R-level
alternative to set.seed() for Mersenne-Twister with a better guarantee
th
1. Have you followed the hints about configuration with Intel compilers
in the R Installation and Administration manual?
2. Havbe you tried R-2.14.2 which is the current reelase version (since
two days)?
Uwe Ligges
On 02.03.2012 14:10, Denis Croizé-Fillon wrote:
Hi,
On a linux (suse 11p1 64
Hi,
On a linux (suse 11p1 64 bits) and intel compiler (11.1 20100806), for R
2.14.1 I ran :
./configure
make
The config.log file is available at
ftp://ftp.ifremer.fr/ifremer/divers_permanents/config.log
Binary file R is created, all seems Ok. However :
make check
fails with the m
> Karl Forner
> on Fri, 2 Mar 2012 10:36:14 +0100 writes:
>> Some of the random number generators allow as a seed a
>> vector, not only a single number. This can simplify
>> generating the seeds. There can be one seed for each of
>> the 1000 runs and then, the rows of
Thanks for your quick reply.
About the rngSetSeed package: is it usable at c/c++ level ?
The same can be said about initializations. Initialization is a random
> number generator, whose output is used as the initial state of some
> other generator. There is no proof that a particular initializati
On Fri, Mar 02, 2012 at 10:36:14AM +0100, Karl Forner wrote:
[...]
> Hello,
> I would be also in favor for using multiple seeds based on (seed,
> task_number) for convenience (i.e. avoiding storing the seeds)
> and with the possibility of having a dynamic number of tasks, but I am mot
> sure it is
On Fri, Mar 02, 2012 at 10:36:14AM +0100, Karl Forner wrote:
[...]
> Hello,
> I would be also in favor for using multiple seeds based on (seed,
> task_number) for convenience (i.e. avoiding storing the seeds)
> and with the possibility of having a dynamic number of tasks, but I am mot
> sure it is
Dear R gurus,
I am interested in permutations-based cpu-intensive methods so I had to pay
a little attention to Random Number Generators (RNG).
For my needs, RNGs have to:
1) be fast. I profiled my algorithms, and for some the bottleneck was
the RNG.
2) be scalable. Meaning that I want the R
> Some of the random number generators allow as a seed a vector,
> not only a single number. This can simplify generating the seeds.
> There can be one seed for each of the 1000 runs and then,
> the rows of the seed matrix can be
>
> c(seed1, 1), c(seed1, 2), ...
> c(seed2, 1), c(seed2, 2), ...
>
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