
# **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.

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

