ergm (version 3.6.1)

control.ergm.bridge: Auxiliary for Controlling ergm.bridge

Description

Auxiliary function as user interface for fine-tuning ergm.bridge algorithm, which approximates log likelihood ratios using bridge sampling.

Usage

control.ergm.bridge(nsteps=20, MCMC.burnin=10000, MCMC.interval=100, MCMC.samplesize=10000,  obs.MCMC.samplesize=MCMC.samplesize, obs.MCMC.interval=MCMC.interval, obs.MCMC.burnin=MCMC.burnin,
                    MCMC.prop.weights="default", MCMC.prop.args=list(),
                    MCMC.init.maxedges=20000, MCMC.packagenames=c(),
                    seed=NULL, parallel=0, parallel.type=NULL, parallel.version.check=TRUE)

Arguments

nsteps

Number of geometric bridges to use.

MCMC.burnin

Number of proposals before any MCMC sampling is done. It typically is set to a fairly large number.

MCMC.interval

Number of proposals between sampled statistics.

MCMC.samplesize

Number of network statistics, randomly drawn from a given distribution on the set of all networks, returned by the Metropolis-Hastings algorithm.

obs.MCMC.burnin, obs.MCMC.interval, obs.MCMC.samplesize

The obs versions of these arguments are for the unobserved data simulation algorithm.

MCMC.prop.weights

Specifies the proposal distribution used in the MCMC Metropolis-Hastings algorithm. Possible choices are "TNT" or "random"; the "default" is one of these two, depending on the constraints in place (as defined by the constraints argument of the ergm function), though not all weights may be used with all constraints. The TNT (tie / no tie) option puts roughly equal weight on selecting a dyad with or without a tie as a candidate for toggling, whereas the random option puts equal weight on all possible dyads, though the interpretation of random may change according to the constraints in place. When no constraints are in place, the default is TNT, which appears to improve Markov chain mixing particularly for networks with a low edge density, as is typical of many realistic social networks.

MCMC.prop.args

An alternative, direct way of specifying additional arguments to proposal.

MCMC.init.maxedges

Maximum number of edges expected in network.

MCMC.packagenames

Names of packages in which to look for change statistic functions in addition to those autodetected. This argument should not be needed outside of very strange setups.

seed

Seed value (integer) for the random number generator. See set.seed

parallel

Number of threads in which to run the sampling. Defaults to 0 (no parallelism). See the entry on parallel processing for details and troubleshooting.

parallel.type

API to use for parallel processing. Supported values are "MPI" and "PSOCK". Defaults to using the parallel package with PSOCK clusters. See ergm-parallel

parallel.version.check

Logical: If TRUE, check that the version of ergm running on the slave nodes is the same as that running on the master node.

Value

A list with arguments as components.

Details

This function is only used within a call to the ergm.bridge.llr or ergm.bridge.dindstart.llk functions.

See Also

ergm.bridge.llr, ergm.bridge.dindstart.llk