***** To join INSNA, visit http://www.insna.org ***** Hi Stanley and Mark, We do indeed owe a lot to Ove Frank. I'm happy for the models to be called exponential random graph models, exponential families of random graphs, or p* models interchangeably. Cheers Garry Dr Garry Robins Department of Psychology School of Behavioural Science University of Melbourne Victoria 3010 Australia Tel: 61 3 8344 4454 Fax: 61 3 9347 6618 Web: www.psych.unimelb.edu.au/people/staff/RobinsG.html Melnet website: http://www.sna.unimelb.edu.au/ -----Original Message----- From: Social Networks Discussion Forum [mailto:[log in to unmask]] On Behalf Of Stanley Wasserman Sent: Monday, 12 February 2007 10:01 AM To: [log in to unmask] Subject: you call them ERGs, we call them p* .... how about Frank-Strauss?? ***** To join INSNA, visit http://www.insna.org ***** Mark: Thanks for correcting me on the dependence structure for p2 --- indeed, it is a model based on dyadic independence, conditional on the nodal attribute variables. With respect to names of distributions .... I suppose I am a traditional guy who feels that original names do not necessarily have to be changed. Paul Holland named p1, who told me that he viewed it as the first cool graph distribution. p* was named to get away from Ove Frank and David Strauss' "Markov random graph" label, since one does not have to have Markov distribution, and because the distribution was so cool, cooler and better than p1, that it deserved a star. As for ERGs ---- if only its practitioners retained the important "family" part of the name. As far as I know, everyone calls it simply an "exponential random graph" model, which is perhaps the most uninformative name of all. All (almost all?) probability mass functions for graphs can be made exponential --- but clearly not all are special exponential FAMILIES. p1, p*, and so forth, refer to specific distributions; the label exponential can be applied to all random graph distributions. I do wish that this class of models was referred to as an exponential family (a special beast in statistics), but not even the recent literature does so. I believe that the recent literature does not call this an exponential family. For example, Snijders, T.A.B., Pattison, P., Robins, G.L., & Handock, M. (In press). New specifications for exponential random graph models. Sociological Methodology. Robins, G., Pattison, P., Kalish, Y., & Lusher, D. (2005). A workshop on exponential random graph (p*) models for social networks. Social Networks. Robins, G., Snijders, T., Wang, P., Handcock, M., & Pattison, P. (2005). Recent developments in Exponential Random Graph (p*) Models for Social Networks. Social Networks. Some of us use the rather long, but certainly more accurate and informative phrase "p*, an exponential family of random graphs". So, since Mark inquired, those are the reasons I do not use this uninformative and uninstructive ERG label. Where's that necessary "family" noun? It would be preferable, and an nice tribute I think, henceforth to refer to this exponential family as Frank-Strauss random graphs, to honor David (and especially Ove) who first used these ideas in network science. We network statisticians owe much to Ove. SW On Feb 9, 2007, at 9:03 PM, Mark S. Handcock wrote: > ***** To join INSNA, visit http://www.insna.org ***** > > To add to Stanley's notes: > > The p2 model does not assume dyad independence. It is explicitly a > dyad > dependence model, although there is conditional independence given the > node-specific random effects. > > The naming of the exponential family models for networks is a bit > problematic. Historically, Holland, Leinhardt and others presented > them as > exponential families of distributions over the space of graphs. The > so-called "p1" model was a particularly useful class presented in > their > seminal paper with an unfortunately uninstructive name (a non-name > really!). > The generalization by Frank and Strauss is a general statistical > exponential > family of distributions over graphs. The specification of the > statistics > constitutes the modeling part. This is the reason recent work > references > them as (statistical) exponential family models. A number of > acronyms or > combination of terms to capture this make sense, and constructively > describe > the statistical roots and connections of the model class. The > utility of the > "p*" name is unclear to me (perhaps Stanley can describe why he > prefers it > to the earlier name?). > > Cheers, > > Mark > > ------------------------------------------------- > Mark S. Handcock > Professor of Statistics > Department of Statistics, C014-B Padelford Hall > University of Washington, Box 354322 Phone: (206) 221-6930 > Seattle, WA 98195-4322. FAX: (360) 365-6324 > Web: www.stat.washington.edu/~handcock > internet: [log in to unmask] > > _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message. _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.