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. The methods are described in Leifeld, Cranmer and Desmarais (2018), JStatSoft <doi:10.18637/jss.v083.i06>.

Version: 1.10.11
Depends: R (≥ 3.5)
Imports: stats, utils, methods, graphics, network (≥ 1.17.1), sna (≥ 2.3.2), ergm (≥ 4.2.1), parallel, Matrix (≥ 1.3.2), boot (≥ 1.3.17), coda (≥ 0.18.1), ROCR (≥ 1.0.7), igraph (≥ 0.7.1), statnet.common (≥ 4.5.0)
Suggests: fastglm (≥ 0.0.1), speedglm (≥ 0.3.1), testthat, Bergm (≥ 5.0.2), RSiena (≥ 1.0.12.232), ggplot2 (≥ 2.0.0)
Published: 2023-10-05
Author: Philip Leifeld [aut, cre], Skyler J. Cranmer [ctb], Bruce A. Desmarais [ctb]
Maintainer: Philip Leifeld <philip.leifeld at essex.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/leifeld/btergm
NeedsCompilation: no
Citation: btergm citation info
CRAN checks: btergm results

Documentation:

Reference manual: btergm.pdf

Downloads:

Package source: btergm_1.10.11.tar.gz
Windows binaries: r-devel: btergm_1.10.11.zip, r-release: btergm_1.10.11.zip, r-oldrel: btergm_1.10.11.zip
macOS binaries: r-release (arm64): btergm_1.10.11.tgz, r-oldrel (arm64): btergm_1.10.11.tgz, r-release (x86_64): btergm_1.10.11.tgz
Old sources: btergm archive

Reverse dependencies:

Reverse imports: ergMargins, netmediate
Reverse suggests: broom
Reverse enhances: texreg

Linking:

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