View source: R/control.ergm.bridge.R
control.ergm.bridge | R Documentation |
ergm.bridge.llr()
and logLik.ergm()
Auxiliary functions as user interfaces for fine-tuning the
ergm.bridge.llr()
algorithm, which approximates log likelihood
ratios using bridge sampling.
By default, the bridge sampler inherits its control
parameters from the ergm()
fit; control.logLik.ergm()
allows
the user to selectively override them.
control.ergm.bridge( bridge.nsteps = 16, bridge.target.se = NULL, bridge.bidirectional = TRUE, MCMC.burnin = MCMC.interval * 128, MCMC.burnin.between = max(ceiling(MCMC.burnin/sqrt(bridge.nsteps)), MCMC.interval * 16), MCMC.interval = 128, MCMC.samplesize = 16384, obs.MCMC.burnin = obs.MCMC.interval * 128, obs.MCMC.burnin.between = max(ceiling(obs.MCMC.burnin/sqrt(bridge.nsteps)), obs.MCMC.interval * 16), obs.MCMC.interval = MCMC.interval, obs.MCMC.samplesize = MCMC.samplesize, MCMC.prop = trim_env(~sparse), MCMC.prop.weights = "default", MCMC.prop.args = list(), obs.MCMC.prop = MCMC.prop, obs.MCMC.prop.weights = MCMC.prop.weights, obs.MCMC.prop.args = MCMC.prop.args, MCMC.maxedges = Inf, MCMC.packagenames = c(), term.options = list(), seed = NULL, parallel = 0, parallel.type = NULL, parallel.version.check = TRUE, parallel.inherit.MT = FALSE, ... ) control.logLik.ergm( bridge.nsteps = 16, bridge.target.se = NULL, bridge.bidirectional = TRUE, MCMC.burnin = NULL, MCMC.interval = NULL, MCMC.samplesize = NULL, obs.MCMC.samplesize = MCMC.samplesize, obs.MCMC.interval = MCMC.interval, obs.MCMC.burnin = MCMC.burnin, MCMC.prop = NULL, MCMC.prop.weights = NULL, MCMC.prop.args = NULL, obs.MCMC.prop = MCMC.prop, obs.MCMC.prop.weights = MCMC.prop.weights, obs.MCMC.prop.args = MCMC.prop.args, MCMC.maxedges = NULL, MCMC.packagenames = NULL, term.options = NULL, seed = NULL, parallel = NULL, parallel.type = NULL, parallel.version.check = TRUE, parallel.inherit.MT = FALSE, ... )
bridge.nsteps |
Number of geometric bridges to use. |
bridge.target.se |
If not |
bridge.bidirectional |
Whether the bridge sampler first bridges from |
MCMC.burnin |
Number of proposals before any MCMC sampling is done. It typically is set to a fairly large number. |
MCMC.burnin.between |
Number of proposals between the bridges; typically, less and less is needed as the number of steps decreases. |
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.burnin.between, obs.MCMC.interval, obs.MCMC.samplesize |
The |
MCMC.prop |
Specifies the proposal (directly) and/or
a series of "hints" about the structure of the model being
sampled. The specification is in the form of a one-sided formula
with hints separated by A common and default "hint" is |
MCMC.prop.weights |
Specifies the proposal
distribution used in the MCMC Metropolis-Hastings algorithm. Possible
choices depending on selected |
MCMC.prop.args |
An alternative, direct way of specifying additional arguments to proposal. |
obs.MCMC.prop, obs.MCMC.prop.weights, obs.MCMC.prop.args |
The |
MCMC.maxedges |
The maximum number of edges that may occur during the MCMC sampling. If this number is exceeded at any time, sampling is stopped immediately. |
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. |
term.options |
A list of additional arguments to be passed to term initializers. See |
seed |
Seed value (integer) for the random number generator. See
|
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 |
parallel.version.check |
Logical: If TRUE, check that the version of
|
parallel.inherit.MT |
Logical: If TRUE, slave nodes and
processes inherit the |
... |
A dummy argument to catch deprecated or mistyped control parameters. |
control.ergm.bridge()
is only used within a call to the
ergm.bridge.llr()
, ergm.bridge.dindstart.llk()
, or
ergm.bridge.0.llk()
functions.
control.logLik.ergm()
is only used within a call to the
logLik.ergm()
.
A list with arguments as components.
ergm.bridge.llr()
logLik.ergm
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