[R] Why R simulation gives same random results?
Prof Brian Ripley
ripley at stats.ox.ac.uk
Thu Feb 21 08:07:51 CET 2013
On 20/02/2013 23:13, Greg Snow wrote:
> To know for sure we need to know how you are running these different R
> sessions, but here are some possibilities:
>
> The help page for "set.seed" says that if no seed exists then the seed is
> set based on the current time (and since 2.14.0 the process ID). So one
> possibility is that 2 of the sessions are started close enough together
> that they get the same seed. Or the difference in time and process ID
> cancel each other out.
That is exceedingly unlikely. We are not told the platform, but AFAIK
on all common R platforms and current versions of R:
- the time is measured to at least msec accuracy.
- times which might cancel out pid differences are many hours apart.
A while ago it was possible on some platforms to get the same seed by
starting two R processes on the same clock tick (within 1/60 or 1/100 s
of each other). But now you are talking about generating a pretty
random unsigned integer with 32 bits to set the seed, so the probability
of coincidence is very small.
> Another possibility (also mentioned in the help page) is that if the seed
> was saved in a previous session then it will be restored in the new
> session, if all the sessions are reading in the same stored session (or
> just the 2 that are the same) then they would start from the same seed.
Much more likely.
> On Tue, Feb 19, 2013 at 6:31 PM, C W <tmrsg11 at gmail.com> wrote:
>
>> Hi, list
>> I am doing 100,000 iterations of Bayesian simulations.
>> What I did is I split it into 4 different R sessions, each one runs 25,000
>> iteration. But two of the sessions gave the simulation result.
This falls within the class of parallel simulations. You would do
better to set carefully selected seeds: see the vignette for package
'parallel'.
>> I did not use any set.seed(). What is going on here?
>>
>> Thanks,
>> Mike
--
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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