Mitchell Centre Seminar Series
| Dates: | 14 February 2018 |
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| Times: | 16:00 - 17:30 |
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| What is it: | Seminar |
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| Organiser: | School of Social Sciences |
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Lampros Bouranis, School of Mathematics and Statistics & Insight Centre for Data Analytics, University College Dublin, Ireland
Bayesian model selection for exponential random graph models via adjusted pseudolikelihoods
This talk is concerned with the issue of model choice for the well-known exponential random graph model, widely used in social network analysis. This amounts to choosing which network statistics to include in the ERG model. However this task is complicated by the fact that the ERG likelihood is intractable. We approach this problem from a Bayesian perspective and propose a tractable approximation of the likelihood using the pseudolikelihood function popularised by Strauss and Ikeda. In particular, we propose a novel adjustment of the pseudolikelihood function so that it is closely matches the ERG likelihood, in a certain sense. This, in turn, allows us to implement widely used computational methods for Bayesian model selection in the context of exponential random graph models for the analysis of real-world social networks. Empirical comparisons to existing methods for various experiments show that our procedure yields similar results to existing methods, but at a fraction of the computational cost. This is joint work with Nial Friel and Florian Maire.
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A114
Samuel Alexander Building
Manchester
