parJagsModel is used to create an object representing a
Bayesian graphical model, specified with a BUGS-language description
of the prior distribution, and a set of data.
parJagsModel(cl, name, file, data=sys.frame(sys.parent()),
inits, n.chains = 1, n.adapt=1000, quiet=FALSE)parJagsModel returns an object inheriting from class jags
which can be used to generate dependent samples from the posterior
distribution of the parameters. These jags models are
residing on the workers, thus updating/sampling is possible.
Length of cl must be equal to or greater than n.chains.
RNG seed generation takes place first on the master,
and chains then initialized on
each worker by distributing inits and single chained models.
An object of class jags is a list of functions that share a
common environment, see jags.model for details.
Data cloning information is attached to the returned
object if data argument has n.clones attribute.
A cluster object created by makeCluster, or
an integer. It can also be NULL,
see parDosa.
Size of the cluster must be equal to or larger than n.chains.
character, name for the model to be assigned on the workers.
the name of the file containing a
description of the model in the
JAGS dialect of the BUGS language.
Alternatively, file can be a readable text-mode connection,
or a complete URL. It can be also a function or a
custommodel object.
a list or environment containing the data. Any numeric
objects in data corresponding to node arrays used in
file are taken to represent the values of observed nodes
in the model
optional specification of initial values in the form of a
list or a function (see Initialization on
help page of jags.model). If omitted,
initial values will be generated automatically. It is an error to
supply an initial value for an observed node.
the number of parallel chains for the model
the number of iterations for adaptation. See
adapt for details. If n.adapt = 0 then no
adaptation takes place.
if TRUE then messages generated during compilation
will be suppressed. Effect of this argument is not visible on the
master process.
Peter Solymos, solymos@ualberta.ca
Original sequential function in rjags:
jags.model
Sequential dclone-ified version: jagsModel
See example on help page of parCodaSamples.