Package: mlergm 0.8

Jonathan Stewart

mlergm: Multilevel Exponential-Family Random Graph Models

Estimates exponential-family random graph models for multilevel network data, assuming the multilevel structure is observed. The scope, at present, covers multilevel models where the set of nodes is nested within known blocks. The estimation method uses Monte-Carlo maximum likelihood estimation (MCMLE) methods to estimate a variety of canonical or curved exponential family models for binary random graphs. MCMLE methods for curved exponential-family random graph models can be found in Hunter and Handcock (2006) <doi:10.1198/106186006X133069>. The package supports parallel computing, and provides methods for assessing goodness-of-fit of models and visualization of networks.

Authors:Jonathan Stewart [cre, aut], Michael Schweinberger [ctb]

mlergm_0.8.tar.gz
mlergm_0.8.tar.gz(r-4.5-noble)mlergm_0.8.tar.gz(r-4.4-noble)
mlergm_0.8.tgz(r-4.4-emscripten)mlergm_0.8.tgz(r-4.3-emscripten)
mlergm.pdf |mlergm.html
mlergm/json (API)

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

Peer review:

Datasets:
  • classes - Polish school classes data set.

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.18 score 1 stars 15 scripts 276 downloads 7 exports 69 dependencies

Last updated 3 years agofrom:467a7a70dd. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-linuxNOTENov 21 2024

Exports:is.gof_mlergmis.mlergmis.mlnetmlergmmlnetset_optionssimulate_mlnet

Dependencies:cachemclicodacolorspacecowplotcpp11crayonDEoptimRdplyrergmevaluatefansifarverfastmapforcatsgenericsGGallyggplot2ggstatsgluegtablehighrhmsisobandknitrlabelinglatticelifecyclelpSolvelpSolveAPImagrittrMASSMatrixmemoisemgcvmunsellnetworknlmepatchworkpillarpkgconfigplyrprettyunitsprogresspurrrR6rbibutilsRColorBrewerRcppRdpackreshape2rlangrlerobustbasescalessnastatnet.commonstringistringrtibbletidyrtidyselecttrustutf8vctrsviridisLitewithrxfunyaml

Tutorial: mlergm

Rendered frommlergm_tutorial.Rmdusingknitr::rmarkdownon Nov 21 2024.

Last update: 2019-05-15
Started: 2018-12-03