control.simulate.network: Auxiliary for Controlling Separable Temporal ERGM Simulation

Description

Auxiliary function as user interface for fine-tuning STERGM simulation.

Usage

control.simulate.network(MCMC.burnin.min = 1000,
  MCMC.burnin.max = 1e+05, MCMC.burnin.pval = 0.5,
  MCMC.burnin.add = 1, MCMC.burnin = NULL, MCMC.burnin.mul = NULL,
  MCMC.prop.weights.form = "default", MCMC.prop.args.form = NULL,
  MCMC.prop.weights.diss = "default", MCMC.prop.args.diss = NULL,
  MCMC.init.maxedges = 20000, MCMC.packagenames = c(),
  term.options = NULL, MCMC.init.maxchanges = 1e+06)
control.simulate.stergm(MCMC.burnin.min = NULL, MCMC.burnin.max = NULL,
  MCMC.burnin.pval = NULL, MCMC.burnin.add = NULL,
  MCMC.burnin = NULL, MCMC.burnin.mul = NULL,
  MCMC.prop.weights.form = NULL, MCMC.prop.args.form = NULL,
  MCMC.prop.weights.diss = NULL, MCMC.prop.args.diss = NULL,
  MCMC.init.maxedges = NULL, MCMC.packagenames = NULL,
  term.options = NULL, MCMC.init.maxchanges = NULL)

Arguments

MCMC.burnin.min, MCMC.burnin.max, MCMC.burnin.pval, MCMC.burnin.add

Number of Metropolis-Hastings steps per phase (formation and dissolution) per time step used in simulation. By default, this is determined adaptively by keeping track of increments in the Hamming distance between the transitioned-from network and the network being sampled (formation network or dissolution network). Once MCMC.burnin.min steps have elapsed, the increments are tested against 0, and when their average number becomes statistically indistinguishable from 0 (with the p-value being greater than MCMC.burnin.pval), or MCMC.burnin.max steps are proposed, whichever comes first, the simulation is stopped after an additional MCMC.burnin.add times the number of elapsed steps had been taken. (Stopping immediately would bias the sampling.)

To use a fixed number of steps, set both MCMC.burnin.min and MCMC.burnin.max to the desired number of steps.

MCMC.burnin, MCMC.burnin.mul

No longer used. See MCMC.burnin.min, MCMC.burnin.max, MCMC.burnin.pval, MCMC.burnin.pval, and MCMC.burnin.add.

MCMC.prop.weights.form, MCMC.prop.weights.diss

Specifies the proposal distribution used in the MCMC Metropolis-Hastings algorithm for formation and dissolution, respectively. Possible choices are "TNT" or "random"; the "default". 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.

MCMC.prop.args.form, MCMC.prop.args.diss

An alternative, direct way of specifying additional arguments to proposals.

MCMC.init.maxedges

Maximum number of edges expected in network.

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. It can also be set globally via option(ergm.term=list(...)).

MCMC.init.maxchanges

Maximum number of toggles changes for which to allocate space.

Value

A list with arguments as components.

Details

This function is only used within a call to the simulate function. See the usage section in simulate.stergm for details.

Description

Usage

Arguments

Value

Details

See Also