Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Temporal Exponential Random Graph Models with btergm: Estimation and Bootstrap Confidence Intervals | Leifeld | Journal of Statistical Software
Authors: Philip Leifeld, Skyler J. Cranmer, Bruce A. Desmarais
Title: Temporal Exponential Random Graph Models with btergm: Estimation and Bootstrap Confidence Intervals
Abstract: The xergm package is an implementation of extensions to the exponential random graph model (ERGM). It acts as a meta-package for multiple constituent packages. One of these packages is btergm, which implements bootstrap methods for the temporal ERGM estimated by maximum pseudolikelihood. Here, we illustrate the temporal exponential random graph model and its implementation in the package btergm using data on international alliances and a longitudinally observed friendship network in a Dutch school.

Page views:: 1121. Submitted: 2014-11-10. Published: 2018-02-22.
Paper: Temporal Exponential Random Graph Models with btergm: Estimation and Bootstrap Confidence Intervals     Download PDF (Downloads: 384)
Supplements:
btergm_1.9.1.tar.gz: R source package Download (Downloads: 53; 57KB)
v83i06.R: R replication code Download (Downloads: 58; 9KB)

DOI: 10.18637/jss.v083.i06

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Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.