Computational statistical methods for Social network models



Publication Details

Hunter, D. R., Krivitsky, P. N.. & Schweinberger, M. (2012). Computational statistical methods for Social network models. Journal of Computational and Graphical Statistics, 21 (4), 856-882.


We review the broad range of recent statistical work in social network models, with emphasis on computational aspects of these methods. Particular focus is applied to exponential-family random graph models (ERGM) and latent variable models for data on complete networks observed at a single time point, though we also briefly review many methods for incompletely observed networks and networks observed at multiple time points. Although we mention far more modeling techniques than we can possibly cover in depth, we provide numerous citations to current literature.We illustrate several of the methods on a small, well-known network dataset, Sampson’s monks, providing code where possible so that these analyses may be duplicated.

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