Bergm: 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: https://acaimo.github.io/Bergm

How to cite Bergm

Caimo, A., Bouranis, L., Krause, R., and Friel, N. (2014). Statistical Network Analysis with Bergm. Journal of Statistical Software, 104(1), 1–23. doi: https://doi.org/10.18637/jss.v104.i01.