R: Auxiliary for Controlling SAN

control.san {ergm} | R Documentation

## Auxiliary for Controlling SAN

### Description

Auxiliary function as user interface for fine-tuning simulated annealing algorithm.

### Usage

    control.san(coef=NULL,

                SAN.tau=1,
                SAN.invcov=NULL,
                SAN.burnin=100000,
                SAN.interval=10000,
                SAN.init.maxedges=20000,

                SAN.prop.weights="default",
                SAN.prop.args=list(),
                SAN.packagenames=c(),

                MPLE.max.dyad.types=1e6,
                MPLE.samplesize = 50000,

                network.output="network",

                seed=NULL,
                parallel=0,
                parallel.type=NULL,
                parallel.version.check=TRUE)

### Arguments

`coef` | Vector of model coefficients used for MCMC simulations, one for each model term.
`SAN.tau` | Currently unused.
`SAN.invcov` | Initial inverse covariance matrix used to calculate Mahalanobis distance in determining how far a proposed MCMC move is from the `target.stats` vector. If NULL, taken to be the covariance matrix returned when fitting the MPLE if `coef==NULL`, or the identity matrix otherwise.
`SAN.burnin` | Number of MCMC proposals before any sampling is done.
`SAN.interval` | Number of proposals between sampled statistics.
`SAN.init.maxedges` | Maximum number of edges expected in network.
`SAN.prop.weights` | Specifies the method to allocate probabilities of being proposed to dyads. Defaults to `"default"`, which picks a reasonable default for the specified constraint. Other possible values are `"TNT"`, `"random"`, and `"nonobserved"`, though not all values may be used with all possible constraints.
`SAN.prop.args` | An alternative, direct way of specifying additional arguments to proposal.
`SAN.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.
`MPLE.max.dyad.types` | Maximum number of unique values of change statistic vectors, which are the predictors in a logistic regression used to calculate the MPLE. This calculation uses a compression algorithm that allocates space based on `MPLE.max.dyad.types`
`MPLE.samplesize` | Not currently documented; used in conditional-on-degree version of MPLE.
`network.output` | R class with which to output networks. The options are "network" (default) and "edgelist.compressed" (which saves space but only supports networks without vertex attributes)
`seed` | Seed value (integer) for the random number generator. See `set.seed`
`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.

### Details

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

### Value

A list with arguments as components.

### See Also

`san`

[Package ergm version 3.8.0 Index]