Statistical Network Analysis with <b>Bergm</b>

Recent advances in computational methods for intractable models have made network data increasingly amenable to statistical analysis. Exponential random graph (ERGMs) emerged as one of the main families capable capturing complex dependence structure a wide range applied contexts. The Bergm package R has become popular carry out Bayesian parameter inference, missing imputation, model selection and goodness-of-fit diagnostics ERGMs. Over last few years, been considerably improved terms efficiency by adopting some state-of-the-art doublyintractable distributions. Recently, version 5 available on CRAN having undergone substantial makeover, which it more accessible easy use practitioners. New functions include augmentation procedures based approximate exchange algorithm dealing with data, adjusted pseudolikelihood pseudo-posterior procedures, allow fast inference ERGM posterior evidence networks several thousands nodes.