ergmm-class {latentnet}

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, 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.list.ergmm