Package: GADAG 0.99.0

Magali Champion

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

GADAG_0.99.0.tar.gz
GADAG_0.99.0.tar.gz(r-4.7-arm64)GADAG_0.99.0.tar.gz(r-4.7-x86_64)GADAG_0.99.0.tar.gz(r-4.6-arm64)GADAG_0.99.0.tar.gz(r-4.6-x86_64)
GADAG_0.99.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
GADAG/json (API)

# Install 'GADAG' in R:
install.packages('GADAG', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

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

openblascpp

1.00 score 6 scripts 600 downloads 5 exports 14 dependencies

Last updated from:40902c5013. Checks:4 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE109
linux-devel-x86_64NOTE115
source / vignettesOK170
linux-release-arm64NOTE115
linux-release-x86_64NOTE125
wasm-releaseOK117

Exports:evaluationfitnessGADAG_AnalyzeGADAG_RungenerateToyData

Dependencies:clicpp11glueigraphlatticelifecyclemagrittrMASSMatrixpkgconfigRcppRcppArmadillorlangvctrs