Exponential Random Graph (p ) Models

specification for one-mode networks. We investigated features of the model by simulation, and compared the goodness of fit results obtained using the maximum likelihood and pseudolikelihood approaches. Examples used in this paper show that the ERGM with the newly specified statistics is a powerful tool for statistical analysis of aliation networks.

[1]  D. Hunter,et al.  Goodness of Fit of Social Network Models , 2008 .

[2]  Garry Robins,et al.  An introduction to exponential random graph (p*) models for social networks , 2007, Soc. Networks.

[3]  David R. Hunter,et al.  Curved exponential family models for social networks , 2007, Soc. Networks.

[4]  Steven M. Goodreau,et al.  Advances in exponential random graph (p*) models applied to a large social network , 2007, Soc. Networks.

[5]  Peng Wang,et al.  Recent developments in exponential random graph (p*) models for social networks , 2007, Soc. Networks.

[6]  H. Robbins.  A Stochastic Approximation Method , 1951 .

[7]  P. Pattison,et al.  New Specifications for Exponential Random Graph Models , 2006 .

[8]  S. Wasserman,et al.  Models and Methods in Social Network Analysis , 2005 .

[9]  P. Pattison,et al.  Small and Other Worlds: Global Network Structures from Local Processes1 , 2005, American Journal of Sociology.

[10]  S. Wasserman,et al.  Models and Methods in Social Network Analysis: An Introduction to Random Graphs, Dependence Graphs, and p * , 2005 .

[11]  P. Pattison,et al.  Models and Methods in Social Network Analysis: Interdependencies and Social Processes: Dependence Graphs and Generalized Dependence Structures , 2005 .

[12]  P. Pattison,et al.  Building models for social space: neighourhood-based models for social networks and affiliation structures , 2004 .

[13]  Garry Robins,et al.  Small Worlds Among Interlocking Directors: Network Structure and Distance in Bipartite Graphs , 2004, Comput. Math. Organ. Theory.

[14]  Tom A. B. Snijders,et al.  DYNAMIC SOCIAL NETWORK MODELING AND ANALYSIS , 2003 .

[15]  P. Pattison,et al.  9. Neighborhood-Based Models for Social Networks , 2002 .

[16]  Tom A. B. Snijders,et al.  Markov Chain Monte Carlo Estimation of Exponential Random Graph Models , 2002, J. Soc. Struct..

[17]  Garry Robins,et al.  Network models for social selection processes , 2001, Soc. Networks.

[18]  S. Wasserman,et al.  Logit models and logistic regressions for social networks: II. Multivariate relations. , 1999, The British journal of mathematical and statistical psychology.

[19]  S. Wasserman,et al.  Logit models and logistic regressions for social networks: III. Valued relations , 1999 .

[20]  John Skvoretz,et al.  8. Logit Models for Affiliation Networks , 1999 .

[21]  S. Wasserman,et al.  Logit models and logistic regressions for social networks: I. An introduction to Markov graphs andp , 1996 .

[22]  C. Geyer,et al.  Constrained Monte Carlo Maximum Likelihood for Dependent Data , 1992 .

[23]  D. J. Strauss,et al.  Pseudolikelihood Estimation for Social Networks , 1990 .

[24]  A. Baddeley,et al.  Nearest-Neighbour Markov Point Processes and Random Sets , 1989 .

[25]  John Scott.  What is social network analysis , 2010 .

[26]  B. Bollobás.  The evolution of random graphs , 1984 .

[27]  P. Holland,et al.  An Exponential Family of Probability Distributions for Directed Graphs , 1981 .

[28]  J. Besag.  Spatial Interaction and the Statistical Analysis of Lattice Systems , 1974 .