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(SAN.maxit = 4, SAN.tau = 1, SAN.invcov = NULL,
      SAN.invcov.diag = FALSE, SAN.nsteps.alloc = function(nsim)
      2^seq_len(nsim), SAN.nsteps = 2^19, SAN.samplesize = 2^12,
      SAN.init.maxedges = 20000, SAN.max.maxedges = 2^26,
      SAN.prop.weights = "default", SAN.prop.args = list(),
      SAN.packagenames = c(), term.options = list(), seed = NULL,
      parallel = 0, parallel.type = NULL, parallel.version.check = TRUE)

### Arguments

`SAN.maxit` | Number of temperature levels to use.
`SAN.tau` | Tuning parameter, specifying the temperature of the process during the penultimate iteration. (During the last iteration, the temperature is set to 0, resulting in a greedy search, and during the previous iterations, the temperature is set to `SAN.tau*(iterations left after this one)`.
`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`, initially set to the identity matrix, then during subsequent runs estimated empirically.
`SAN.invcov.diag` | Whether to only use the diagonal of the covariance matrix. It seems to work better in practice.
`SAN.nsteps.alloc` | Either a numeric vector or a function of the number of runs giving a sequence of relative lengths of simulated annealing runs.
`SAN.nsteps` | Number of MCMC proposals for all the annealing runs combined.
`SAN.samplesize` | Number of realisations' statistics to obtain for tuning purposes.
`SAN.init.maxedges` | Maximum number of edges expected in network.
`SAN.max.maxedges` | Hard upper bound on the number of edges in the 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.
`term.options` | A list of additional arguments to be passed to term initializers. It can also be set globally via `option(ergm.term=list(...))`.
`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 3.10.4 Index]