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]