Re: [R] Random seed problem in MCMC coupling of chains

Dimitris Rizopoulos Wed, 08 Jun 2005 06:54:37 -0700

do you want something like this:

niter <- 3
nchain <- 2
rs <- sample(500, niter, TRUE)
for (i in 1:niter) { # iterations
 for (j in 1:nchain) { # chains
   set.seed(rs[i])
   a <- runif(1)
   cat("iter:", i, "chain:", j, "runif:", a, "\n")
 }
}



I hope it helps.

Best,
Dimitris

----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/16/336899
Fax: +32/16/337015
Web: http://www.med.kuleuven.ac.be/biostat/
    http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm

----- Original Message -----From: "Gorjanc Gregor" <[EMAIL PROTECTED]>

To: <r-help@stat.math.ethz.ch>
Sent: Wednesday, June 08, 2005 3:27 PM
Subject: [R] Random seed problem in MCMC coupling of chains

Hello!

I am performing coupling of chains in MCMC and I need the same value
of seed for two chains. I will show demo of what I want:

R code, which might show my example is:
niter <- 3
nchain <- 2
tmpSeed <- 123
for (i in 1:niter) { # iterations
 for (j in 1:nchain) { # chains
   set.seed(tmpSeed)
   a <- runif(1)
   cat("iter:", i, "chain:", j, "runif:", a, "\n")
   tmpSeed <- .Random.seed
 }
}

I get this:

iter: 1 chain: 1 runif: 0.43588
iter: 1 chain: 2 runif: 0.43588
iter: 2 chain: 1 runif: 0.43588
iter: 2 chain: 2 runif: 0.43588
iter: 3 chain: 1 runif: 0.43588
iter: 3 chain: 2 runif: 0.43588

but I would like to get:

iter: 1 chain: 1 runif: 0.43588
iter: 1 chain: 2 runif: 0.43588
iter: 2 chain: 1 runif: 0.67676
iter: 2 chain: 2 runif: 0.67676
iter: 3 chain: 1 runif: 0.12368
iter: 3 chain: 2 runif: 0.12368

Note that seed value is of course changing, but it is parallel
between chains.

I am able to do only this, since setting seed at the beginning
of chain i.e iteration is not a problem, but I want an upper
scheme, since I compare chains and stop one if some condition is
satisfied.

tmpSeed <- 123
for (i in 1:nchain) { # chains
 set.seed(tmpSeed)
 for (j in 1:niter) { # iterations
   a <- runif(1)
   cat("iter:", j, "chain:", i, "runif:", a, "\n")
 }
}
iter: 1 chain: 1 runif: 0.28758
iter: 2 chain: 1 runif: 0.7883
iter: 3 chain: 1 runif: 0.40898
iter: 1 chain: 2 runif: 0.28758
iter: 2 chain: 2 runif: 0.7883
iter: 3 chain: 2 runif: 0.40898
iter: 1 chain: 3 runif: 0.28758
iter: 2 chain: 3 runif: 0.7883
iter: 3 chain: 3 runif: 0.40898

I was looking in 'rlecuyer', 'rsprng' and 'setRNG', but did not find
anything usable for me.  From reading on http://sprng.cs.fsu.edu/
'rsprng' provides just opposite of what I want, 'rlecuyer' is a bit
to technical for me, but I think it also doesn't give identical
seed for parallels. 'setRNG', especially it's function 'getRNG()'
looks nice but its arguments should have seed stored. How can one
do that?


Thanks in advance!

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 knowit,

you have no certainty until you try." Sophocles ~ 450 B.C.

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Re: [R] Random seed problem in MCMC coupling of chains

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