Recent developments in exponential random graph (p*) models for social networks

Social Networks

Volumn 29, Issue 2, 2007, Pages 192-215

  Robins, Garry ^a   Snijders, Tom ^b   Wang, Peng ^a   Handcock, Mark ^c   Pattison, Philippa ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b UNIVERSITY OF GRONINGEN   (Netherlands)

^c UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Exponential random graph models; p* models; Statistical models for social networks

Indexed keywords

EID: 34147152799     PISSN: 03788733     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.socnet.2006.08.003     Document Type: Article

References (28)

1. Boer, P., Huisman, M., Snijders, T.A.B., Wichers, L.H.Y., Zeggelink, E., 2006. StOCNET: an open software system for the advanced analysis of social networks. Version 1.7. ICS/Science Plus, Groningen.
2. Borgatti S., Everett M., and Freeman L. UCINET 5 for Windows: Software for Social Network Analysis (1999), Analytic Technologies, Harvard, MA
3. Butts C.T. Memory Structures for Relational Data in R: Classes and Interfaces Working Paper (2002), Department of Sociology, UC-Irvine
4. Butts C.T. The Network Package. Manual (2005), Department of Sociology, UC-Irvine. http://erzuli.ss.uci.edu/R.stuff (URL: http://erzuli.ss.uci.edu/R.stuff)
5. Frank O. Statistical analysis of change in networks. Statistica Neerlandica 45 (1991) 283-293
6. Frank O., and Strauss D. Markov graphs. Journal of the American Statistical Association 81 (1986) 832-842
7. Geyer C.J., and Thompson E.A. Constrained Monte Carlo maximum likelihood calculations (with discussion). Journal of the Royal Statistical Society, Series C 54 (1992) 657-699
8. *) models to a large social network. Social Networks 29 (2007) 231-248
9. Handcock M.S. Statistical models for social networks: degeneracy and inference. In: Breiger R., Carley K., and Pattison P. (Eds). Dynamic Social Network Modeling and Analysis (2003), National Academies Press, Washington, DC 229-240
10. Handcock, M.S., 2003b. Assessing degeneracy in statistical models of social networks. Center for Statistics and the Social Sciences. Working Paper No. 39.
11. Handcock M., Hunter D., Butts C., Goodreau S., and Morris M. Statnet: An R Package for the Statistical Modeling of Social Networks (2004), Manual, University of Washington. http://www.csde.washington.edu/statnet (URL: http://www.csde.washington.edu/statnet)
12. Hunter D. Curved exponential family models for social networks. Social Networks 29 (2007) 216-230
13. Hunter D., and Handcock M. Inference in curved exponential family models for networks. Journal of Computational and Graphical Statistics 15 (2006) 565-583
14. Park J., and Newman M. Solution of the 2-star model of a network. Physical Review E 70 (2004) 066146
15. Pattison P.E., and Robins G.L. Neighbourhood-based models for social networks. Sociological Methodology 32 (2002) 301-337
16. Pattison P.E., and Wasserman S. Logit models and logistic regressions for social networks: II. Multivariate relations. British Journal of Mathematical and Statistical Psychology 52 (1999) 169-194
17. *) models for social networks. Social Networks 29 (2007) 173-191
18. Robins G.L., Pattison P.E., and Wasserman S. Logit models and logistic regressions for social networks, III. Valued relations. Psychometrika 64 (1999) 371-394
19. Robins G.L., Pattison P.E., and Woolcock J. Social networks and small worlds. American Journal of Sociology 110 (2005) 894-936
20. Snijders T.A.B. Markov chain Monte Carlo estimation of exponential random graph models. Journal of Social Structure 3 (2002) 2
21. Snijders T.A.B., and van Duijn M.A.J. Conditional maximum likelihood estimation under various specifications of exponential random graph models. In: Jan Hagberg (Ed). Contributions to Social Network Analysis, Information Theory, and Other Topics: A Festschrift in Honour of Ove Frank (2002), Department of Statistics, University of Stockholm 117-134
22. Snijders T.A.B., Pattison P., Robins G.L., and Handcock M. New specifications for exponential random graph models. Sociological Methodology (2006)
23. Snijders T.A.B., Steglich C.E.G., Schweinberger M., and Huisman M. Manual of SIENA Version 2.1 (2005), ICS, University of Groningen, Groningen
24. Strauss D. On a general class of models for interaction. SIAM Review 28 (1986) 513-527
25. Strauss D., and Ikeda M. Pseudo-likelihood estimation for social networks. Journal of the American Statistical Association 85 (1990) 204-212
26. Wang P., Robins G., and Pattison P. Pnet: A Program for the Simulation and Estimation of Exponential Random Graph Models (2006), University of Melbourne
27. Wasserman S., and Pattison P.E. Logit models and logistic regressions for social networks: I. An introduction to Markov graphs and p*. Psychometrika 61 (1996) 401-425
28. Wasserman S., and Robins G.L. An introduction to random graphs, dependence graphs, and p*. In: Carrington P., Scott J., and Wasserman S. (Eds). Models and Methods in Social Network Analysis (2005), Cambridge University Press, New York 148-161