  In this paper we describe the main featuress of the Bergm package for the
open-source R software which provides a comprehensive framework for Bayesian
analysis for 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 two
well-known network datasets.
