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

TLDR

Network data analysis is a rapidly expanding field within and beyond statistics. The paper reviews key statistical network models, aiming to inform readers and guide further study. The review summarizes models and illustrates them with the Zachary karate dataset, highlighting available software implementations. © 2012 Wiley Periodicals, Inc., Statistical Analysis and Data Mining, 2012.

Abstract

Abstract 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