作者
Alberto Caimo, Nial Friel
发表日期
2014
期刊
Journal of Statistical Software
卷号
61
期号
2
简介
The Bergm package provides a comprehensive framework for Bayesian inference using Markov chain Monte Carlo (MCMC) algorithms. It can also supply graphical Bayesian goodness-of-fit procedures that address the issue of model adequacy. The package is simple to use and represents an attractive way of analysing network data as it offers the advantage of a complete probabilistic treatment of uncertainty. Bergm is based on the ergm package and therefore it makes use of the same model set-up and network simulation algorithms. The Bergm package has been continually improved in terms of speed performance over the last years and now offers the end-user a feasible option for carrying out Bayesian inference for networks with several thousands of nodes.
学术搜索中的文章
A Caimo, N Friel - arXiv preprint arXiv:1201.2770, 2012
A Caimo, N Friel - arXiv preprint arXiv:1703.05144, 2017