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ergm.userterms: A Template Package for Extending statnet

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  • Hunter, David R.
  • Goodreau, Steven M.
  • Handcock, Mark S.

Abstract

Exponential-family random graph models (ERGMs) represent a powerful and flexible class of models for the statistical analysis of networks. statnet is a suite of software packages that implement these models. This paper details how the capabilities for ERGM modeling can be expanded and customized by programming additional network statistics that may be included in ERGMs. We describe a template R package called ergm.userterms that can be modified for this purpose. It is designed to make this process as straightforward as possible. We also explain some of the internal workings of statnet that will help users develop their own network analysis capabilities.

Suggested Citation

  • Hunter, David R. & Goodreau, Steven M. & Handcock, Mark S., 2013. "ergm.userterms: A Template Package for Extending statnet," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i02).
    • Handle: RePEc:jss:jstsof:v:052:i02
    DOI: http://hdl.handle.net/10.18637/jss.v052.i02
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    References listed on IDEAS

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    1. Hunter, David R. & Handcock, Mark S. & Butts, Carter T. & Goodreau, Steven M. & Morris, Martina, 2008. "ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i03).
    2. Morris, Martina & Handcock, Mark S. & Hunter, David R., 2008. "Specification of Exponential-Family Random Graph Models: Terms and Computational Aspects," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i04).
    3. Butts, Carter T., 2008. "network: A Package for Managing Relational Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i02).
    4. Handcock, Mark S. & Hunter, David R. & Butts, Carter T. & Goodreau, Steven M. & Morris, Martina, 2008. "statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i01).
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    Cited by:

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