Review of statistical network analysis: models, algorithms, and software

Michael Salter-Townshend, Arthur White, Isabella Gollini, Thomas Brendan Murphy

Research output: Contribution to journalArticle (Academic Journal)peer-review

82 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)243-264
JournalStatistical Analysis and Data Mining
Issue number4
Publication statusPublished - 2012


Dive into the research topics of 'Review of statistical network analysis: models, algorithms, and software'. Together they form a unique fingerprint.

Cite this