R: Auxiliary for Controlling Separable Temporal ERGM Simulation

control.simulate.stergm {tergm} | R Documentation

## Auxiliary for Controlling Separable Temporal ERGM Simulation

### Description

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

### Usage

    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)

### 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.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.maxchanges` | Maximum number of toggles changes for which to allocate space.
`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.
`MCMC.init.maxedges` | Maximum number of edges expected in network.
`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`.

### Details

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

### Value

A list with arguments as components.

### See Also

`simulate.stergm`, `simulate.formula`. `control.stergm` performs a similar function for `stergm`.

[Package tergm version 3.4.1 Index]