Auxiliary function as user interface for fine-tuning ERGM
simulation. control.simulate
, control.simulate.formula
, and
control.simulate.formula.ergm
are all aliases for the same
function.
While the others supply a full set of simulation
settings, control.simulate.ergm
when passed as a control
parameter to simulate.ergm()
allows some settings to be
inherited from the ERGM stimation while overriding others.
control.simulate.formula.ergm(MCMC.burnin = 10000,
MCMC.interval = 1000, MCMC.prop.weights = "default",
MCMC.prop.args = list(), MCMC.init.maxedges = 20000,
MCMC.packagenames = c(), MCMC.runtime.traceplot = FALSE,
network.output = "network", term.options = NULL, parallel = 0,
parallel.type = NULL, parallel.version.check = TRUE, ...)control.simulate(MCMC.burnin = 10000, MCMC.interval = 1000,
MCMC.prop.weights = "default", MCMC.prop.args = list(),
MCMC.init.maxedges = 20000, MCMC.packagenames = c(),
MCMC.runtime.traceplot = FALSE, network.output = "network",
term.options = NULL, parallel = 0, parallel.type = NULL,
parallel.version.check = TRUE, ...)
control.simulate.formula(MCMC.burnin = 10000, MCMC.interval = 1000,
MCMC.prop.weights = "default", MCMC.prop.args = list(),
MCMC.init.maxedges = 20000, MCMC.packagenames = c(),
MCMC.runtime.traceplot = FALSE, network.output = "network",
term.options = NULL, parallel = 0, parallel.type = NULL,
parallel.version.check = TRUE, ...)
control.simulate.ergm(MCMC.burnin = NULL, MCMC.interval = NULL,
MCMC.prop.weights = NULL, MCMC.prop.args = NULL,
MCMC.init.maxedges = NULL, MCMC.packagenames = NULL,
MCMC.runtime.traceplot = FALSE, network.output = "network",
term.options = NULL, parallel = 0, parallel.type = NULL,
parallel.version.check = TRUE, ...)
Number of proposals before any MCMC sampling is done. It typically is set to a fairly large number.
Number of proposals between sampled statistics.
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.
Logical: If TRUE, plot traceplots of the MCMC sample after every MCMC MLE iteration.
R class with which to output networks. The options are "network" (default) and "edgelist.compressed" (which saves space but only supports networks without vertex attributes)
A list of additional arguments to be passed to term initializers. It can also be set globally via option(ergm.term=list(...))
.
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.
Additional arguments, passed to other functions This argument is helpful because it collects any control parameters that have been deprecated; a warning message is printed in case of deprecated arguments.
A list with arguments as components.
This function is only used within a call to the simulate
function. See the usage
section in simulate.ergm
for
details.
simulate.ergm
, simulate.formula
.
control.ergm
performs a similar function for
ergm
; control.gof
performs a similar function
for gof
.