Bayesian computational algorithms for social network analysis
arXiv:1504.03152
Abstract
In this chapter we review some of the most recent computational advances in the rapidly expanding field of statistical social network analysis using the R open-source software. In particular we will focus on Bayesian estimation for two important families of models: exponential random graph models (ERGMs) and latent space models (LSMs).
Book chapter to appear in "Challenges of Computational Network Analysis With R"