simulate: Draw from the distribution of an Exponential Random Graph Mixed Model

Description

If passed a ergmm fit object, simulate is used to simulate networks from the posterior of an exponetial random graph mixed model fit. Alternatively, a ergmm.model object can be passed to simulate based on a particular parametr configuration.

Usage

## S3 method for class 'ergmm':
simulate(object, nsim = 1, seed = NULL,\dots)
## S3 method for class 'ergmm.model':
simulate(object,nsim=1,seed=NULL,par,prior=list(),...)

Arguments

object

either an object of class ergmm for posterior simulation, or an object of class ergmm.model for a specific model.

nsim

number of networks to draw (independently)

seed

random seed to use; defaults to using the current state of the random number generator

par

a list with the parameter configuration based on which to simulate

prior

a list with the prior distribution parameters that deviate from their defaults

...

Additional arguments. Currently unused.

Value

If nsim = 1, simulate returns an object of class network. Otherwise, an object of class network.series that is a list consisting of the following elements:
$formulaThe formula used to generate the sample.
$networksA list of the generated networks.

Details

A sample of networks is randomly drawn from the specified model. If a needed value of par is missing, it is generated from its prior distribution.

Examples

Run this code

#
# Fit a short MCMC run: just the MCMC.
#
data(sampson)
gest <- ergmm(samplike ~ euclidean(d=2,G=3),
              control=ergmm.control(burnin=100,interval=5,sample.size=100),tofit="mcmc")
#
# Draw from the posterior
#
g.sim <- simulate(gest)
plot(g.sim)
#
# Draw from the first draw from the posterior
#
g.sim <- with(gest,simulate(model,par=sample[[1]],prior=prior))
plot(g.sim)