(This article was originally published at Three-Toed Sloth , and syndicated at StatsBlogs.)

Attention conservation notice: Only of interest if you (1) care about statistical models of networks, and (2) will be in Pittsburgh on Monday.

Constant readers will recall that I have often in the past boosted Mark
Handcock's work
on comparing
distributions, measuring
trends in
inequality, doing
sensible inference with power laws,
and modeling network structure
statistically. I am thus *extremely* happy to announce next week's
seminar:

- Mark Handcock, "Exponential-family Random Network Models for Social Networks"
*Abstract:*Random graphs, where the connections between nodes are considered random variables, have wide applicability in the social sciences. Exponential-family Random Graph Models (ERGM) have shown themselves to be a useful class of models for representing complex social phenomena.- We generalize ERGM by also modeling the attributes of the social actors as random variates, thus creating a random model of both the relational and individual data, which we call Exponential-family Random Network Models (ERNM).
- This provides a framework for expanded analysis of network processes, including a new formulation for network progression, where the outcomes, covariates and relations are socially endogenous. In this talk, we focus on a new class of latent cluster models and network regression.
- (Joint work with Ian M. Fellows.)
*Time and place:*4--5 pm on Monday, 12 November 2012, in the Adamson Wing (Room 136) of Baker Hall

As always, the talk is free and open to the public.

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