| ergmm.object {latentnet} | R Documentation |
Class of Fitted Exponential Random Graph Mixed Models
Description
A class ergmm to represent a fitted exponential random graph
mixed model. The output of ergmm.
Details
There are methods summary.ergmm, print.ergmm,
plot.ergmm, predict.ergmm,
as.mcmc.ergmm, and as.mcmc.list.ergmm.
The structure of ergmm is as follows:
sample- An object of class
ergmm.par.list containing the
MCMC sample from the posterior. If the run had multiple threads, their output is concatenated.
mcmc.mle- A list containing the parameter
configuration of the highest-likelihood MCMC iteration.
mcmc.pmode- A list containing the parameter
configuration of the highest-joint-density (conditional on cluster
assignments) MCMC iteration.
mkl- A list containing the MKL estimate.
model- A list containing the model
that was fitted.
prior- A 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.
control- A 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.
mle- A list containing the MLE,
conditioned on cluster assignments.
pmode- A list containing the posterior mode,
conditioned on cluster assignments.
burnin.start- A list containing the starting
value for the burnin.
main.start- A list (or a list of lists, for a
multithreaded run) containing the starting
value for the sampling.
See Also
ergmm,
summary.ergmm,
plot.ergmm,
predict.ergmm,
as.mcmc.ergmm,
as.mcmc.list.ergmm
[Package
latentnet version 2.2-2
Index]