Assessing Goodness of Fit of Exponential Random Graph Models

Yin Li, Keumhee Chough Carriere

Abstract


Exponential Random Graph Models (ERGMs) have been developed for fitting social network data on both static and dynamic levels. However, lack of methods with large sample asymptotic properties makes it inadequate to assess the goodness of fit of these ERGMs. Simulation-based goodness of fit plots proposed by Hunter et al. (2006) compare structured statistics of observed network with those of corresponding simulated networks. In this paper, we propose a new approach to assessing the goodness of fit of ERGMs. We demonstrate how to improve the existing graphical techniques via simulation studies. We also propose a simulation-based test statistic that will assist in model comparisons.

Full Text: PDF DOI: 10.5539/ijsp.v2n4p64

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International Journal of Statistics and Probability   ISSN 1927-7032(Print)   ISSN 1927-7040(Online)

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