Thanks to Paul and Gabor for additional tips/examples. Actually, I find
Pauls suggestion with setRNG also nice and is exactly what I wanted.
Paul, if I understand this correctly, your suggestion with setRNG does not
alter "RNG flow", it just takes care that chains really have equal seeds.
I remember that I have read somewhere that destroying "RNG flow over and
over to get real randomness" is not a good idea. Can someone confirm this?
niter <- 3
nchain <- 2
for (i in 1:niter) { # iterations
tmpSeed <- setRNG()
for (j in 1:nchain) { # chains
setRNG(tmpSeed)
a <- runif(1)
cat("iter:", i, "chain:", j, "runif:", a, "\n")
}
}
iter: 1 chain: 1 runif: 0.8160078
iter: 1 chain: 2 runif: 0.8160078
iter: 2 chain: 1 runif: 0.4909793
iter: 2 chain: 2 runif: 0.4909793
iter: 3 chain: 1 runif: 0.4425924
iter: 3 chain: 2 runif: 0.4425924
[... removed other stuff ...]
Lep pozdrav / With regards,
Gregor Gorjanc
----------------------------------------------------------------------
University of Ljubljana
Biotechnical Faculty URI: http://www.bfro.uni-lj.si/MR/ggorjan
Zootechnical Department mail: gregor.gorjanc <at> bfro.uni-lj.si
Groblje 3 tel: +386 (0)1 72 17 861
SI-1230 Domzale fax: +386 (0)1 72 17 888
Slovenia, Europe
----------------------------------------------------------------------
"One must learn by doing the thing; for though you think you know it,
you have no certainty until you try." Sophocles ~ 450 B.C.
______________________________________________
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
