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.

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.