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 parallel uses in the > environment. > > In case you don't want to wrestle with attachments, the same files are > online in our SVN > > http://winstat.quant.ku.edu/svn/hpcexample/trunk/Ex66-ParallelSeedPrototype/
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 simple old approach of setting the seeds within each run with a formula like set.seed(2345 + 10 * run) Answer: That does allow replication, but it does not assure that each run uses non-overlapping random number streams. It offers absolutely no assurance whatsoever that the runs are actually non-redundant. The following demonstrates that the function set.seed() for the default generator indeed allows to have correlated streams. step <- function(x) { x[x < 0] <- x[x < 0] + 2^32 x <- (69069 * x + 1) %% 2^32 x[x > 2^31] <- x[x > 2^31] - 2^32 x } n <- 1000 seed1 <- 124370417 # any seed seed2 <- step(seed1) set.seed(seed1) x <- runif(n) set.seed(seed2) y <- runif(n) rbind(seed1, seed2) table(x[-1] == y[-n]) The output is [,1] seed1 124370417 seed2 205739774 FALSE TRUE 5 994 This means that if the streams x, y are generated from the two seeds above, then y is almost exactly equal to x shifted by 1. What is the current state of your project? Petr Savicky. ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
