### "Exponential-family Random Network Models for Social Networks" (Next Week at the Statistics Seminar)

*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.

Networks;
Enigmas of Chance

Posted at November 08, 2012 12:15 | permanent link