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 2.2-3
Index]