Package: GADAG 0.99.0

GADAG: A Genetic Algorithm for Learning Directed Acyclic Graphs

Sparse large Directed Acyclic Graphs learning with a combination of a convex program and a tailored genetic algorithm (see Champion et al. (2017) <https://hal.archives-ouvertes.fr/hal-01172745v2/document>).

Authors:Magali Champion, Victor Picheny and Matthieu Vignes

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

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

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

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

5 exports 0.00 score 14 dependencies 6 scripts 700 downloads

Last updated 7 years agofrom:40902c5013. Checks:OK: 4 NOTE: 5. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 28 2024
R-4.5-win-x86_64NOTEAug 28 2024
R-4.5-linux-x86_64NOTEAug 28 2024
R-4.4-win-x86_64NOTEAug 28 2024
R-4.4-mac-x86_64NOTEAug 28 2024
R-4.4-mac-aarch64NOTEAug 28 2024
R-4.3-win-x86_64OKAug 28 2024
R-4.3-mac-x86_64OKAug 28 2024
R-4.3-mac-aarch64OKAug 28 2024

Exports:evaluationfitnessGADAG_AnalyzeGADAG_RungenerateToyData

Dependencies:clicpp11glueigraphlatticelifecyclemagrittrMASSMatrixpkgconfigRcppRcppArmadillorlangvctrs