R: Use Simulated Annealing to attempt to match a network to a...

san {ergm}

R Documentation

Use Simulated Annealing to attempt to match a network to a vector of mean statistics

Description

This function attempts to find a network or networks whose statistics match those passed in via the meanstats vector.

Usage

## S3 method for class 'formula'
san(object, nsim=1, seed=NULL, theta0=NULL,
                      tau=1, invcov=NULL,
                      burnin=10000, interval=10000,
                      meanstats=NULL,
                      basis=NULL,
                      sequential=TRUE,
                      constraints = ~.,
                      control = control.san(),
                      verbose=FALSE, ...)
## S3 method for class 'ergm'
san(object, nsim=1, seed=NULL, theta0=object$coef,
                      burnin=10000, interval=10000, 
                      meanstats=NULL,
                      basis=NULL,
                      sequential=TRUE,
                      constraints = NULL,
                      control = control.san(),
                      verbose=FALSE, ...)

Arguments

`object`	an R object. Either a `formula` or an `ergm` object. The `formula` should be of the form `y ~ <model terms>`, where `y` is a network object or a matrix that can be coerced to a `network` object. For the details on the possible `<model terms>`, see `ergm-terms`. To create a `network` object in R, use the `network()` function, then add nodal attributes to it using the `%v%` operator if necessary.
`nsim`	Number of desired networks.
`seed`	Random number integer seed.
`theta0`	Parameter values used for MCMC simulations.
`tau`	Currently unused.
`invcov`	Initial inverse covariance matrix used to calculate Mahalanobis distance in determining how far a proposed MCMC move is from the `meanstats` vector. If NULL, taken to be the covariance matrix returned when fitting the MPLE (if `theta0==NULL`) or the identity (otherwise).
`burnin`	Number of MCMC steps prior to recording first vector of network statistics.
`interval`	Number of MCMC steps between recordings of network statistics
`meanstats`	A vector of the same length as the number of terms implied by the formula, which is either `object` itself in the case of `san.formula` or `object$formula` in the case of `san.ergm`.
`basis`	If not NULL, a network that forms the beginning of the Markov chain. If NULL, this is taken to be the network named in the formula.
`sequential`	Logical: Should the returned draws use the prior draw as the starting network or always use the initially passed network?
`constraints`	A one-sided formula specifying one or more constraints on the support of the distribution of the networks being simulated. See the documentation for a similar argument for `ergm` for more information. For `simulate.formula`, defaults to no constraints. For `simulate.ergm`, defaults to using the same constraints as those with which `object` was fitted.
`control`	A list of control parameters for algorithm tuning. Constructed using `control.san`.
`verbose`	If this is `TRUE`, we will print out more information as we run the program, including (currently) some goodness of fit statistics.
`...`	Further arguments passed to or used by methods.

Value

A network or list of networks that hopefully have network statistics close to the meanstats vector.

[Package ergm version 2.4-3 Index]