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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>).
Version: | 0.99.0 |
Depends: | igraph, MASS |
Imports: | Rcpp (≥ 0.12.5) |
LinkingTo: | Rcpp, RcppArmadillo |
Published: | 2017-04-11 |
DOI: | 10.32614/CRAN.package.GADAG |
Author: | Magali Champion, Victor Picheny and Matthieu Vignes |
Maintainer: | Magali Champion <magali.champion at parisdescartes.fr> |
License: | GPL-2 |
NeedsCompilation: | yes |
CRAN checks: | GADAG results |
Reference manual: | GADAG.pdf |
Package source: | GADAG_0.99.0.tar.gz |
Windows binaries: | r-devel: GADAG_0.99.0.zip, r-release: GADAG_0.99.0.zip, r-oldrel: GADAG_0.99.0.zip |
macOS binaries: | r-release (arm64): GADAG_0.99.0.tgz, r-oldrel (arm64): GADAG_0.99.0.tgz, r-release (x86_64): GADAG_0.99.0.tgz, r-oldrel (x86_64): GADAG_0.99.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.