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 <tmrs...@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, rip...@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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