R: Draw from the distribution of an Exponential Random Graph...
simulate
R Documentation
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,...)
## 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.
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.
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:
$formula
The formula used to generate the sample.
$networks
A list of the generated networks.
See Also
ergmm, network, print.network
Examples
#
# 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)