Bayesian computational algorithms for social network analysis
Computation
2015-04-14 v1
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).
Cite
@article{arxiv.1504.03152,
title = {Bayesian computational algorithms for social network analysis},
author = {Alberto Caimo and Isabella Gollini},
journal= {arXiv preprint arXiv:1504.03152},
year = {2015}
}
Comments
Book chapter to appear in "Challenges of Computational Network Analysis With R"