Auxiliary function as user interface for fine-tuning ergm.bridge algorithm, which approximates log likelihood ratios using bridge sampling.
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)
Number of geometric bridges to use.
Number of proposals before any MCMC sampling is done. It typically is set to a fairly large number.
Number of proposals between sampled statistics.
Number of network statistics, randomly drawn from a given distribution on the set of all networks, returned by the Metropolis-Hastings algorithm.
The obs versions of these arguments are for the unobserved
data simulation algorithm.
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.
An alternative, direct way of specifying additional arguments to proposal.
Maximum number of edges expected in network.
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 value (integer) for the random number generator.
See set.seed
Number of threads in which to run the sampling. Defaults to 0 (no parallelism). See the entry on parallel processing for details and troubleshooting.
API to use for parallel
processing. Supported values are "MPI" and
"PSOCK". Defaults to using the parallel package with PSOCK clusters. See
ergm-parallel
Logical: If TRUE, check that the version of
ergm running on the slave nodes is the
same as that running on the master node.
A list with arguments as components.
This function is only used within a call to the ergm.bridge.llr
or ergm.bridge.dindstart.llk functions.