CMU-ISR-10-130
Institute for Software Research
School of Computer Science, Carnegie Mellon University



CMU-ISR-10-130

The LInk Probability Model: A Network
Simulation Alternative to the Exponential
Random Graph Model

Ian McCulloh*, Joshua Lospinoso**, Kathleen M. Carley

December 2010

CMU-ISR-10-130.pdf

Center for the Computational Analysis of Social and Organizational Systems
CASOS Technical Report


Keywords: Exponential random graph models, p* models, statistical models for social networks, degeneracy, longitudinal social network analysis.


The Link Probability Model (LPM) can be used as an alternative to Exponential Random Graph Models (ERGM) to simulate network data. The LPM characterizes the networks in terms of link probabilities based on historical frequencies. In this paper, the LPM is presented, compared and contrasted with the ERGM. The relative utility of the two approaches is examined by applying both to four longitudinal data sets. The relative strengths and weaknesses of the two approaches in terms of data requirements, scalability, and assumptions are described.

21 pages

*School of Information Science, Curtin University of Australia, Perth, Western Australia
**Department of Statistics, Oxford University, Oxford, England


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