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Activity Number: 404
Type: Invited
Date/Time: Tuesday, August 2, 2016 : 2:00 PM to 3:50 PM
Sponsor: International Indian Statistical Association
Abstract #318402
Title: Alternatives to Exponential-Family Models for Social Networks
Author(s): Mark Stephen Handcock*
Companies: University of California at Los Angeles
Keywords: random graph models ; social networks ; Markov chain Monte Carlo ; statistical exponential families ; social sciences
Abstract:

Major barriers to the stochastic modeling of social networks are the specification of realistic models, the computational difficulties of the inferential methods, and assessment of the goodness-of-fit. Exponential-family Random Graph Models (ERGM) have shown themselves to be a useful class of models for representing complex social phenomena. However, they suffer from these and other deficiencies.

In this talk we discuss alternatives to ERGM that retain many of their desirable properties while addressing their deficiencies.


Authors who are presenting talks have a * after their name.

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