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:
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')) |
- 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.
Last updated 3 years agofrom:467a7a70dd. Checks:OK: 1 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 21 2024 |
R-4.5-linux | NOTE | Dec 21 2024 |
Exports:is.gof_mlergmis.mlergmis.mlnetmlergmmlnetset_optionssimulate_mlnet
Dependencies:cachemclicodacolorspacecowplotcpp11crayonDEoptimRdplyrergmevaluatefansifarverfastmapforcatsgenericsGGallyggplot2ggstatsgluegtablehighrhmsisobandknitrlabelinglatticelifecyclelpSolvelpSolveAPImagrittrMASSMatrixmemoisemgcvmunsellnetworknlmepatchworkpillarpkgconfigplyrprettyunitsprogresspurrrR6rbibutilsRColorBrewerRcppRdpackreshape2rlangrlerobustbasescalessnastatnet.commonstringistringrtibbletidyrtidyselecttrustutf8vctrsviridisLitewithrxfunyaml
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Polish school classes data set. | classes |
Evaluate the goodness-of-fit of an estimated model. | gof.mlergm |
Check if object is of class 'gof_mlergm' | is.gof_mlergm |
Determine whether a vector is in the closure of the convex hull of some sample of vectors | is.inCHv3.9 |
Check if the object is of class 'mlergm' | is.mlergm |
Check if object is of class 'mlnet' | is.mlnet |
Multilevel Exponential-Family Random Graph Models | mlergm print.mlergm summary.mlergm |
Multilevel Network | mlnet plot.mlnet |
Plot goodness-of-fit results | plot.gof_mlergm |
Print summary of a 'gof_mlergm' object. | print.gof_mlergm |
Set and adjust options and settings. | set_options |
Simulate a multilevel network | simulate_mlnet |