Auxiliary function as user interface for fine-tuning STERGM simulation.
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,
MCMC.init.maxchanges=NULL)control.simulate.network(MCMC.burnin.min=1000, MCMC.burnin.max=100000,
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(),
MCMC.init.maxchanges=1000000)
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.
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.
An alternative, direct way of specifying additional arguments to proposals.
Maximum number of toggles changes for which to allocate space.
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.
Maximum number of edges expected in network.
No longer used. See
MCMC.burnin.min, MCMC.burnin.max,
MCMC.burnin.pval, MCMC.burnin.pval, and
MCMC.burnin.add.
A list with arguments as components.
This function is only used within a call to the simulate function.
See the usage section in simulate.stergm for details.
simulate.stergm, simulate.formula.
control.stergm performs a
similar function for
stergm.