This material is based upon work supported by the Science Foundation Ireland under Grant No. 08/SRC/I1407: Clique: Graph & Network Analysis Cluster.
Review of statistical network analysis: models, algorithms, and software†
Article first published online: 3 MAY 2012
Copyright © 2012 Wiley Periodicals, Inc.
Statistical Analysis and Data Mining: The ASA Data Science Journal
Volume 5, Issue 4, pages 243–264, August 2012
How to Cite
Salter-Townshend, M., White, A., Gollini, I. and Murphy, T. B. (2012), Review of statistical network analysis: models, algorithms, and software. Statistical Analy Data Mining, 5: 243–264. doi: 10.1002/sam.11146
- Issue published online: 19 JUL 2012
- Article first published online: 3 MAY 2012
- Manuscript Accepted: 19 MAR 2012
- Manuscript Revised: 27 FEB 2012
- Manuscript Received: 3 NOV 2011
- social network analysis;
- latent space model;
- latent position cluster model;
- mixed membership stochastic blockmodel
The analysis of network data is an area that is rapidly growing, both within and outside of the discipline of statistics.
This review provides a concise summary of methods and models used in the statistical analysis of network data, including the Erdős–Renyi model, the exponential family class of network models, and recently developed latent variable models. Many of the methods and models are illustrated by application to the well-known Zachary karate dataset. Software routines available for implementing methods are emphasized throughout.
The aim of this paper is to provide a review with enough detail about many common classes of network models to whet the appetite and to point the way to further reading. © 2012 Wiley Periodicals, Inc. Statistical Analysis and Data Mining, 2012