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: 1.11.1 Depends: R (≥ 3.5) Imports: stats, utils, methods, graphics, network (≥ 1.19.0), sna (≥ 2.8), ergm (≥ 4.8.1), parallel, Matrix (≥ 1.3.2), boot (≥ 1.3.17), coda (≥ 0.18.1), ROCR (≥ 1.0.7), igraph (≥ 2.1.2), statnet.common (≥ 4.11.0) Suggests: fastglm (≥ 0.0.1), speedglm (≥ 0.3.1), testthat, Bergm (≥ 5.0.7), RSiena (≥ 1.0.12.232), ggplot2 (≥ 2.0.0) Published: 2025-03-19 DOI: 10.32614/CRAN.package.btergm Author: Philip Leifeld [aut, cre], Skyler J. Cranmer [ctb], Bruce A. Desmarais [ctb] Maintainer: Philip Leifeld <philip.leifeld at manchester.ac.uk> License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://github.com/leifeld/btergm NeedsCompilation: no Citation: btergm citation info In views: NetworkAnalysis CRAN checks: btergm results [issues need fixing before 2025-08-26]RetroSearch is an open source project built by @garambo | Open a GitHub Issue
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