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Bayesian Analysis of Dynamic Network Regression with Joint Edge / Vertex Dynamics
| Content Provider | Semantic Scholar |
|---|---|
| Copyright Year | 2014 |
| Abstract | Change in network structure and composition has been a topic of extensive theoretical and methodological interest over the last two decades; however, the effects of endogenous group change on interaction dynamics within the context of social networks is a surprisingly understudied area. Network dynamics may be viewed as a process of change in the edge structure of a network, in the vertex set on which edges are defined, or in both simultaneously. Recently, Almquist and Butts (2014) introduced a simple family of models for network panel data with vertex dynamics—referred to here as dynamic network logistic regression (DNR)—expanding on a subfamily of temporal exponential-family random graph models (TERGM) (see Robins and Pattison, 2001; Hanneke |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://users.stat.umn.edu/~almquist/articles/almquist_BC1.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Almquist shell Graph - visual representation Logistic regression Panel data Random graph Social network Subfamily Vertex exponential |
| Content Type | Text |
| Resource Type | Article |
