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
> 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
> 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), ...
>
On Wed, Feb 22, 2012 at 12:17:25PM -0600, Paul Johnson wrote:
[...]
> In order for this to be easy for users, I need to put the init streams
> and set current stream functions into a package, and then streamline
> the process of creating the seed array. My opinion is that CRAN is
> now overflowed
Greetings. Answers below.
On Tue, Feb 21, 2012 at 7:04 AM, Petr Savicky wrote:
>
> Hi.
>
> In the description of your project in the file
>
> http://winstat.quant.ku.edu/svn/hpcexample/trunk/Ex66-ParallelSeedPrototype/README
>
> you argue as follows
>
> Question: Why is this better than the si
On Fri, Feb 17, 2012 at 02:57:26PM -0600, Paul Johnson wrote:
> I've got another edition of my simulation replication framework. I'm
> attaching 2 R files and pasting in the readme.
>
> I would especially like to know if I'm doing anything that breaks
> .Random.seed or other things that R's paral
On Sat, Feb 18, 2012 at 4:33 PM, Paul Johnson wrote:
> On Fri, Feb 17, 2012 at 5:06 PM, Petr Savicky wrote:
>> On Fri, Feb 17, 2012 at 02:57:26PM -0600, Paul Johnson wrote:
>> Hi.
>>
>> Some of the random number generators allow as a seed a vector,
>> not only a single number. This can simplify g
On Fri, Feb 17, 2012 at 09:33:33PM -0600, Paul Johnson wrote:
[...]
> The seed things I'm using are the 6 integer values from the L'Ecuyer.
> If you run the example script, the verbose option causes some to print
> out. The first 3 seeds in a saved project seeds file looks like:
>
> > projSeeds[[
On Fri, Feb 17, 2012 at 5:06 PM, Petr Savicky wrote:
> On Fri, Feb 17, 2012 at 02:57:26PM -0600, Paul Johnson wrote:
> Hi.
>
> 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
On Fri, Feb 17, 2012 at 02:57:26PM -0600, Paul Johnson wrote:
> I've got another edition of my simulation replication framework. I'm
> attaching 2 R files and pasting in the readme.
>
> I would especially like to know if I'm doing anything that breaks
> .Random.seed or other things that R's paral
Ok, I guess I need to look more carefully.
Thanks,
Paul
On 12-02-17 04:44 PM, Paul Johnson wrote:
On Fri, Feb 17, 2012 at 3:23 PM, Paul Gilbert wrote:
Paul
I think (perhaps incorrectly) of the general problem being that one wants to
run a random experiment, on a single node, or two nodes, or
On Fri, Feb 17, 2012 at 3:23 PM, Paul Gilbert wrote:
> Paul
>
> I think (perhaps incorrectly) of the general problem being that one wants to
> run a random experiment, on a single node, or two nodes, or ten nodes, or
> any number of nodes, and reliably be able to reproduce the experiment
> without
Paul
I think (perhaps incorrectly) of the general problem being that one
wants to run a random experiment, on a single node, or two nodes, or ten
nodes, or any number of nodes, and reliably be able to reproduce the
experiment without concern about how many nodes it runs on when you
re-run it.
I've got another edition of my simulation replication framework. I'm
attaching 2 R files and pasting in the readme.
I would especially like to know if I'm doing anything that breaks
.Random.seed or other things that R's parallel uses in the
environment.
In case you don't want to wrestle with att
17 matches
Mail list logo
