2 citations · 3 across the 2 of their papers we have counts for
4 papers
Statistical Network Analysis with Bergm
Alberto Caimo, Lampros Bouranis, Robert Krause +1
Recent advances in computational methods for intractable models have made network data increasingly amenable to statistical analysis. Exponential random graph models (ERGMs) emerge…
A multilayer exponential random graph modelling approach for weighted networks
Alberto Caimo, Isabella Gollini
A new modelling approach for the analysis of weighted networks with ordinal/polytomous dyadic values is introduced. Specifically, it is proposed to model the weighted network conne…
Bergm: Bayesian exponential random graph models in R
Alberto Caimo, Nial Friel
The Bergm package provides a comprehensive framework for Bayesian inference using Markov chain Monte Carlo (MCMC) algorithms. It can also supply graphical Bayesian goodness-of-fit…
Bayesian computational algorithms for social network analysis
Alberto Caimo, Isabella Gollini
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…