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. As described in Leifeld, Cranmer and Desmarais (2018), JStatSoft <doi:10.18637/jss.v083.i06>.
| Version: |
1.10.6 |
| Depends: |
R (≥ 3.5) |
| Imports: |
stats, utils, methods, graphics, network (≥ 1.17.1), sna (≥
2.3.2), ergm (≥ 4.0.1), parallel, Matrix (≥ 1.3.2), boot (≥
1.3.17), coda (≥ 0.18.1), ROCR (≥ 1.0.7), speedglm (≥
0.3.1), igraph (≥ 0.7.1), statnet.common (≥ 4.5.0) |
| Suggests: |
fastglm (≥ 0.0.1), testthat, Bergm (≥ 5.0.2), RSiena (≥
1.0.12.232), ggplot2 (≥ 2.0.0) |
| Published: |
2022-04-02 |
| 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 |