R: Class of Fitted Exponential Random Graph Mixed Models

ergmm-class {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`, 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`

[Package latentnet version 2.10.5 Index]