control.gofN.ergm {ergm.multi}

Auxiliary for Controlling Multinetwork ERGM Linear Goodness-of-Fit Evaluation

Description

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().

Usage

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
)

Arguments

nsim

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.

obs.twostage

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:

1. Sample networks from the model without the observational constraint.

2. 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.

array.max

Try to avoid creating arrays larger in size (in megabytes) than this. Is ignored if save_stats is passed.

simulate, obs.simulate

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.

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.

parallel.inherit.MT

Logical: If TRUE, slave nodes and processes inherit the set.MT_terms() setting.

Details

Auxiliary function as user interface for fine-tuning ERGM Goodness-of-Fit Evaluation.