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latentnet (version 2.0)

ergmm.object: 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.

Arguments

Details

There are methods summary.ergmm, plot.ergmm, predict.ergmm, as.mcmc.ergmm, and as.mcmc.list.ergmm. The structure of ergmm is as follows: ll{ samples 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 An object of class ergmm.par containing the parameter configuration of the highest-likelihood MCMC iteration. mcmc.pmode An object of class ergmm.par containing the parameter configuration of the highest-joint-density (conditional on cluster assignments) MCMC iteration. mkl An object of class ergmm.par containing the MKL estimate. model An object of class ergmm.model 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 An object of class ergmm.par containing the MLE, conditioned on cluster assignments. pmode An object of class ergmm.par containing the posterior mode, conditioned on cluster assignments. burnin.start An object of class ergmm.par containing the starting value for the burnin. main.start An object (or a list of objects, for a multithreaded run) of class ergmm.par containing the starting value for the sampling. }

See Also

ergmm, summary.ergmm, plot.ergmm, predict.ergmm, as.mcmc.ergmm, as.mcmc.list.ergmm