ergm 4: New features

Abstract

The ergm package supports the statistical analysis and simulation of network data. It anchors the statnet suite of packages for network analysis in R introduced in a special issue in Journal of Statistical Software in 2008. This article provides an overview of the new functionality in the 2021 release of ergm version 4. These include more flexible handling of nodal covariates, term operators that extend and simplify model specification, new models for networks with valued edges, improved handling of constraints on the sample space of networks, and estimation with missing edge data. We also identify the new packages in the statnet suite that extend ergm's functionality to other network data types and structural features and the robust set of online resources that support the statnet development process and applications.

Computational improvements discussion in the previous version was split out into another preprint; 30 pages, 2 figures

References in corpus (3)

• Modeling social networks from sampled data
• ergm 4: Computational Improvements
• Improving ERGM Starting Values Using Simulated Annealing

Cited by in corpus (4)

• A Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks
• Improving exponential-family random graph models for bipartite networks
• ALAAMEE: Open-source software for fitting autologistic actor attribute models
• Rejoinder to Discussion of "A Tale of Two Datasets: Representativeness and Generalisability of Inference for Samples of Networks''