A class ergmm to represent a fitted exponential
random graph mixed model. The output of ergmm.
There are methods summary.ergmm, print.ergmm,
plot.ergmm, predict.ergmm, and
as.mcmc.list.ergmm.
The structure of ergmm is as follows:
sampleAn object of class ergmm.par.list containing the
MCMC sample from the posterior. If the run had multiple threads, their output is concatenated.
mcmc.mleA list containing the parameter configuration of the highest-likelihood MCMC iteration.
mcmc.pmodeA list containing the parameter configuration of the highest-joint-density (conditional on cluster assignments) MCMC iteration.
mklA list containing the MKL estimate.
modelA list containing the model that was fitted.
priorA list containing the
information about the prior distribution used. It can be passed as
parameter prior to ergmm to reproduce the prior
in a new fit.
controlA list containing the
information about the model fit settings that do not affect the
posterior distribution. It can be passed as
parameter control to ergmm to reproduce control
parameters in a new fit.
mleA list containing the MLE, conditioned on cluster assignments.
pmodeA list containing the posterior mode, conditioned on cluster assignments.
burnin.startA list containing the starting value for the burnin.
main.startA list (or a list of lists, for a multithreaded run) containing the starting value for the sampling.
ergmm, summary.ergmm,
plot.ergmm, predict.ergmm,
as.mcmc.list.ergmm