Bayesian Exponential Random Graph Models

Set of tools to analyse Bayesian exponential random graph models.


Bergm provides a comprehensive framework for Bayesian parameter estimation and model selection for exponential random graph models using advanged computational algorithms. It can also supply graphical Bayesian goodness-of-fit procedures that address the issue of model adequacy and missing data imputation.

Website: http://acaimo.github.io/Bergm


How to cite Bergm

Alberto Caimo, Nial Friel (2014). Bergm: Bayesian Exponential Random Graphs in R. Journal of Statistical Software, 61(2), 1-25. URL http://www.jstatsoft.org/v61/i02/.

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Reference manual

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install.packages("Bergm")

4.2.0 by Alberto Caimo, 5 months ago


http://acaimo.github.io/Bergm/


Browse source code at https://github.com/cran/Bergm


Authors: Alberto Caimo [aut, cre] , Lampros Bouranis [aut] , Robert Krause [aut] Nial Friel [ctb]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports network, coda, MCMCpack, Matrix, mvtnorm

Depends on ergm


See at CRAN