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Patrick Wolfe

 

 

(http://www.ucl.ac.uk/statistics/people/patrickwolfe)

UCL Statistics

 

Wednesday 21st November 2012

Time: 4pm

 

B10 Basement Seminar Room

Alexandra House, 17 Queen Square, London, WC1N 3AR

 

 

Modelling Network Data

Networks are fast becoming a primary object of interest in statistical data analysis, with important applications spanning the social, biological, and information sciences.  A common aim across these fields is to test for and explain the presence of structure in network data. In this talk we show how characterizing the structural features of a network corresponds to estimating the parameters of various random network models, allowing us to obtain new results for likelihood-based inference and uncertainty quantification in this context.  We discuss asymptotics for stochastic blockmodels with growing numbers of classes, the determination of confidence sets for network structure, and a more general point process modeling for network data taking the form of repeated interactions between senders and receivers, where we show consistency and asymptotic normality of partial-likelihood-based estimators related to the Cox proportional hazards model (arXiv:1201.5871, 1105.6245, 1011.4644, 1011.1703).