Mark S. Handcock
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Human Sciences and Complexity - UC Four Campus Complexity Videoconference Friday February 22, 2008 HANDCOCK: "A simple model for complex networks with arbitrary degree distribution and clustering" powerpoint pdf, with Martina Morris. InterSci wiki R Paper Examples: Using R to replicate a published study
Running the simple model for complex networks with arbitrary degree distribution and clustering in R
Application: David Krackhardt and Mark S. Handcock 2007 Heider vs Simmel: Emergent Features in Dynamic Structures Lecture Notes in Computer Science 4503: 14-27.
Mark S. Handcock is Professor and Chair of Statistics at the University of Washington. He is a core faculty member of the Center for Statistics and the Social Sciences. His work focuses on the development of statistical models for the analysis of social network data, epidemiology, spatial processes and demography. He received his Ph.D. from the University of Chicago. He is a principal author of the statnet R code, which focuses on statistical modeling of network data through ergms, latent space and latent cluster models.
The R software package statnet: software tools for the representation, visualization, analysis and simulation of social network data.
The R software package latentnet: software to fit and evaluate latent position and cluster models for statistical networks.
The preface, data sets, and software to implement the methods in Mark S. Handcock and Martina Morris, 1999, Relative Distribution Methods in the Social Sciences, are available from the Relative Distribution website. Review: http://sankhya.isical.ac.in/search/62b3/62b3rev3.pdf
CSSS Working Paper no. 42 ([PDF(544K bytes )] "New specifications for exponential random graph models" Tom A.B. Snijders, Philippa E. Pattison, Garry L. Robbins and Mark S. Handcock
New specifications for exponential random graph models. Sociological Methodology. Snijders, T.A.B., Steglich, C.E.G., Schweinberger, M., Huisman, M., 2005
