parallel: Get initial values for parallel RNGs
In mcmc-jags/rjags: Bayesian Graphical Models using MCMC

Description Usage Arguments Value Note Author(s) See Also Examples

On a multi-processor system, you may wish to run parallel chains using multiple jags.model objects, each running a single chain on a separate processor. This function returns a list of values that may be used to initialize the random number generator of each chain.

1	parallel.seeds(factory, nchain)

`factory`	Name of the RNG factory to use.
`nchain`	Number of chains for which to initialize RNGs.

parallel.seeds returns a list of RNG states. Each element is a list of length 2 with the following elements:

`.RNG.name`	The name of the RNG
`.RNG.state`	An integer vector giving the state of the RNG.

To make the results of parallel.seeds reproducible, the function jags.seed should be called first.

Martyn Plummer

jags.model, section “Random number generators”, for further details on RNG initialization; list.factories to find the names of available RNG factories. jags.seed to set the seed for the random number generators used by JAGS.

##The BaseRNG factory generates up to four distinct types of RNG. If
##more than 4 chains are requested, it will recycle the RNG types, but
##use different initial values
parallel.seeds("base::BaseRNG", 4)

## The lecuyer module provides the RngStream factory, which allows large
## numbers of independent parallel RNGs to be generated. 
load.module("lecuyer")
list.factories(type="rng")
parallel.seeds("lecuyer::RngStream", 5);