Package: Bergm 5.0.7

Bergm: Bayesian Exponential Random Graph Models

Bayesian analysis for exponential random graph models using advanced computational algorithms. More information can be found at: <https://acaimo.github.io/Bergm/>.

Authors:Alberto Caimo [aut, cre], Lampros Bouranis [aut], Robert Krause [aut] Nial Friel [ctb]

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Bergm.pdf |Bergm.html✨
Bergm/json (API)

# Install 'Bergm' in R:
install.packages('Bergm', repos = c('https://acaimo.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/acaimo/bergm/issues

Datasets:
  • lazega - Lazega lawyers network data

On CRAN:

8 exports 16 stars 2.57 score 88 dependencies 4 dependents 30 scripts 1.2k downloads

Last updated 5 days agofrom:b812f0d290. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 13 2024
R-4.5-winWARNINGSep 13 2024
R-4.5-linuxWARNINGSep 13 2024
R-4.4-winWARNINGSep 13 2024
R-4.4-macWARNINGSep 13 2024
R-4.3-winWARNINGSep 13 2024
R-4.3-macWARNINGSep 13 2024

Exports:bergmbergmCbergmMbgofergmAPLevidenceevidenceCJevidencePP

Dependencies:backportsbitbit64bootbroomcachemclicliprcodacodetoolscpp11crayonDEoptimRdplyrergmevaluatefansifastmapforcatsforeachgenericsglmnetgluehavenhighrhmsiteratorsjomoknitrlatticelifecyclelme4lpSolveAPImagrittrMASSMatrixmatrixcalcMatrixModelsmcmcMCMCpackmemoisemiceminqamitmlmvtnormnetworknlmenloptrnnetnumDerivordinalpanpillarpkgconfigprettyunitsprogresspurrrquantregR6rbibutilsRcppRcppEigenRdpackreadrRglpkrlangrlerobustbaserpartshapeslamSparseMstatnet.commonstringistringrsurvivaltibbletidyrtidyselecttrusttzdbucminfutf8vctrsvroomwithrxfunyaml