Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Bergm: Bayesian Exponential Random Graphs in R | Caimo | Journal of Statistical Software
Authors: Alberto Caimo, Nial Friel
Title: Bergm: Bayesian Exponential Random Graphs in R
Abstract: In this paper we describe the main features of the Bergm package for the open-source R software which provides a comprehensive framework for Bayesian analysis of exponential random graph models: tools for parameter estimation, model selection and goodness-of- fit diagnostics. We illustrate the capabilities of this package describing the algorithms through a tutorial analysis of three network datasets.

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Paper: Bergm: Bayesian Exponential Random Graphs in R     Download PDF (Downloads: 2360)
Supplements:
Bergm_3.0.tar.gz: R source package Download (Downloads: 179; 10KB)
v61i02.R: R example code from the paper Download (Downloads: 178; 3KB)
v61i02-data.zip: Zipped data files Download (Downloads: 175; 1KB)
DOI: 10.18637/jss.v061.i02

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.