ergm 4: New features
Pavel N. Krivitsky (1), David R. Hunter (2), Martina Morris (3), Chad, Klumb (3) ((1) University of New South Wales, (2) Penn State University, (3), University of Washington)
TL;DR
The paper introduces new features in ergm 4, enhancing network data analysis with flexible covariate handling, new models, and better support for various network types and missing data.
Contribution
It presents the 2021 release of ergm 4 with significant new functionalities for network analysis, including advanced modeling and data handling capabilities.
Findings
Enhanced handling of nodal covariates
New models for valued edges
Improved support for missing data
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.
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Taxonomy
TopicsMental Health Research Topics · Complex Network Analysis Techniques · Statistical Methods and Bayesian Inference