btergm: Temporal Exponential Random Graph Models by Bootstrapped Pseudolikelihood

Temporal Exponential Random Graph Models (TERGM) estimated by maximum pseudolikelihood with bootstrapped confidence intervals or Markov Chain Monte Carlo maximum likelihood. Goodness of fit assessment for ERGMs, TERGMs, and SAOMs. Micro-level interpretation of ERGMs and TERGMs.

Version: 1.9.1
Depends: R (≥ 2.14.0), xergm.common (≥ 1.7.7), ggplot2 (≥ 2.0.0)
Imports: stats4, utils, methods, graphics, statnet (≥ 2015.11.0), statnet.common (≥ 3.3.0), network (≥ 1.13.0), sna (≥ 2.3.2), ergm (≥ 3.5.1), texreg (≥ 1.34.4), parallel, Matrix (≥ 1.2.2), boot (≥ 1.3.17), coda (≥ 0.18.1), stats, ROCR (≥ 1.0.7), speedglm (≥ 0.3.1), igraph (≥ 0.7.1), RSiena (≥
Published: 2018-02-15
Author: Philip Leifeld [aut, cre], Skyler J. Cranmer [ctb], Bruce A. Desmarais [ctb]
Maintainer: Philip Leifeld <philip.leifeld at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: btergm citation info
CRAN checks: btergm results


Reference manual: btergm.pdf
Package source: btergm_1.9.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: btergm_1.9.1.tgz
OS X Mavericks binaries: r-oldrel: btergm_1.9.0.tgz
Old sources: btergm archive

Reverse dependencies:

Reverse depends: xergm
Reverse suggests: broom, texreg


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