control.gofN.ergm (or its alias, control.gofN) is
intended to be used with gofN() specifically and will "inherit"
as many control parameters from ergm fit as possible().
control.gofN.ergm(
nsim = 100,
obs.twostage = nsim/2,
array.max = 128,
simulate = control.simulate.ergm(),
obs.simulate = control.simulate.ergm(),
parallel = 0,
parallel.type = NULL,
parallel.version.check = TRUE,
parallel.inherit.MT = FALSE
)control.gofN(
nsim = 100,
obs.twostage = nsim/2,
array.max = 128,
simulate = control.simulate.ergm(),
obs.simulate = control.simulate.ergm(),
parallel = 0,
parallel.type = NULL,
parallel.version.check = TRUE,
parallel.inherit.MT = FALSE
)
Number of networks to be randomly drawn using Markov chain Monte Carlo. This sample of networks provides the basis for comparing the model to the observed network.
Either FALSE or an integer. This parameter
only has an effect if the network has missing data or
observational process. For such networks, evaluating the Pearson
residual requires simulating the expected value of the
conditional variance under the observation process. If FALSE,
the simulation is performed conditional on the observed
network. However, a more accurate estimate can be obtained via a
two-stage process:
Sample networks from the model without the observational constraint.
Conditional on each of those networks, sample with the observational constraint, estimating the variance within each sample and then averaging over the first-stage sample.
Then, obs.twostage specifies the number of unconstrained networks
to simulate from, which should divide the control.gofN.ergm()'s
nsim argument evenly.
Try to avoid creating arrays larger in size (in
megabytes) than this. Is ignored if save_stats is passed.
Control lists produced by
control.simulate.ergm() or equivalent for unconstrained and
constrained simulation, respectively. Parameters are inherited
from the model fit and can be overridden here.
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.
Logical: If TRUE, slave nodes and
processes inherit the set.MT_terms() setting.
Auxiliary function as user interface for fine-tuning ERGM Goodness-of-Fit Evaluation.