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SUMMARY:Modelling Network Data - Patrick J Wolfe\, Professor of Statistics
  at University College London
DTSTART:20120229T140000Z
DTEND:20120229T150000Z
UID:TALK36755@talks.cam.ac.uk
CONTACT:Rachel Fogg
DESCRIPTION:Networks are fast becoming a primary object of interest in sta
 tistical 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 t
 his talk we show how characterizing the structural features of a network c
 orresponds to estimating the parameters of various random network models\,
  allowing us to obtain new results for likelihood-based inference and unce
 rtainty quantification in this context.  We discuss asymptotics for stocha
 stic blockmodels with growing numbers of classes\, the determination of co
 nfidence sets for network structure\, and a more general point process mod
 eling for network data taking the form of repeated interactions between se
 nders and receivers\, where we show consistency and asymptotic normality o
 f partial-likelihood-based estimators related to the Cox proportional haza
 rds model (arXiv:1201.5871\, 1105.6245\, 1011.4644\, 1011.1703).
LOCATION:LR12\, Engineering\, Department of
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