Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina GrĂ¼n, Edzer Pebesma & Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks | Hunter | Journal of Statistical Software
Authors: David R. Hunter, Mark S. Handcock, Carter T. Butts, Steven M. Goodreau, Martina Morris
Title: ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks
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.

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Paper: ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks     Download PDF (Downloads: 21453)
Supplements:
ergm_2.1.tar.gz: R source package Download (Downloads: 2582; 522KB)
v24i03.R: R example code from the paper Download (Downloads: 3302; 2KB)

DOI: 10.18637/jss.v024.i03

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.