simulate.ergmm {latentnet} | 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
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 |
nsim |
number of networks to draw (independently) |
seed |
random seed to use; defaults to using the current state of the random number generator |
... |
Additional arguments. Currently unused. |
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 |
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)