Bayesian analysis for exponential random graph models using
advanced computational algorithms: the approximate exchange algorithm
with adaptive direction sampling (optionally adaptive, delayed-acceptance
and parallel), calibrated pseudo-posteriors, Bayesian
data augmentation for missing network data, and Bayesian goodness-of-fit
diagnostics. More information can be found at:
<https://acaimo.github.io/Bergm/>.
| Version: |
6.0.0 |
| Depends: |
ergm (≥ 4.2.3), R (≥ 4.1) |
| Imports: |
coda, graphics, grDevices, mice, network, parallel, Rcpp, stats, utils |
| LinkingTo: |
Rcpp |
| Suggests: |
spelling, testthat (≥ 3.0.0) |
| Published: |
2026-10-27 |
| DOI: |
10.32614/CRAN.package.Bergm |
| Author: |
Alberto Caimo [aut, cre],
Lampros Bouranis [aut],
Robert Krause [aut],
Isabella Gollini [aut],
Nial Friel [ctb] |
| Maintainer: |
Alberto Caimo <alberto.caimo1 at ucd.ie> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://acaimo.github.io/Bergm/ |
| NeedsCompilation: |
yes |
| Language: |
en-US |
| Citation: |
Bergm citation info |
| Materials: |
README, NEWS |
| In views: |
Bayesian, NetworkAnalysis |
| CRAN checks: |
Bergm results |