ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks

David R. Hunter, Mark S. Handcock, Carter T. Butts, Steven M. Goodreau and Martina Morris

Journal of Statistical Software, 2008, vol. 024, issue i03

Abstract: We describe some of the capabilities of the ergm package and the statistical theory underlying it. This package contains tools for accomplishing three important, and inter-related, tasks involving exponential-family random graph models (ERGMs): estimation, simulation, and goodness of fit. More precisely, ergm has the capability of approximating a maximum likelihood estimator for an ERGM given a network data set; simulating new network data sets from a fitted ERGM using Markov chain Monte Carlo; and assessing how well a fitted ERGM does at capturing characteristics of a particular network data set.

Date: 2008-05-05
References: Add references at CitEc
Citations: View citations in EconPapers (82)

Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v024i03/v24i03.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... 4i03/ergm_2.1.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v024i03/v24i03.R

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:024:i03

DOI: 10.18637/jss.v024.i03

Access Statistics for this article

Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis

More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().