parSetFactory: Advanced control over JAGS on parallel workers

In dclone: Data Cloning and MCMC Tools for Maximum Likelihood Methods

Description

JAGS modules contain factory objects for samplers, monitors, and random number generators for a JAGS model. These functions allow fine-grained control over which factories are active on parallel workers.

Usage

parListFactories(cl, type)
parSetFactory(cl, name, type, state)

Arguments

cl	a cluster object created by the parallel (or snow) package.
name	name of the factory to set
type	type of factory to query or set. Possible values are "sampler", "monitor", or "rng"
state	a logical. If TRUE then the factory will be active, otherwise the factory will become inactive.

Value

parListFactories returns a a list of data frame with two columns per each worker, the first column shows the names of the factory objects in the currently loaded modules, and the second column is a logical vector indicating whether the corresponding factory is active or not.

sparStFactory is called to change the future behaviour of factory objects. If a factory is set to inactive then it will be skipped.

Note

When a module is loaded, all of its factory objects are active. This is also true if a module is unloaded and then reloaded.

Author(s)

Peter Solymos, [e-mail]

See Also

list.modules, set.factory

Examples

## Not run: 
if (require(rjags)) {
cl <- makePSOCKcluster(3)
parListFactories(cl, "sampler")
parListFactories(cl, "monitor")
parListFactories(cl, "rng")
parSetFactory(cl, "base::Slice", "sampler", FALSE)
parListFactories(cl, "sampler")
parSetFactory(cl, "base::Slice", "sampler", TRUE)
stopCluster(cl)
}

## End(Not run)

dclone documentation built on May 2, 2019, 6:08 p.m.