discretecdAlgorithm: Coordinate-Descent Algorithm for Learning Sparse Discrete Bayesian Networks

Structure learning of Bayesian network using coordinate-descent algorithm. This algorithm is designed for discrete network assuming a multinomial data set, and we use a multi-logit model to do the regression. The algorithm is described in Gu, Fu and Zhou (2016) <arXiv:1403.2310>.

Version: 0.0.7
Depends: R (≥ 3.2.3)
Imports: Rcpp (≥ 0.11.0), sparsebnUtils (≥ 0.0.4), igraph
LinkingTo: Rcpp, RcppEigen
Suggests: testthat
Published: 2020-03-12
Author: Jiaying Gu [aut, cre]
Maintainer: Jiaying Gu <gujy.lola at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: C++11
Materials: README
CRAN checks: discretecdAlgorithm results


Reference manual: discretecdAlgorithm.pdf


Package source: discretecdAlgorithm_0.0.7.tar.gz
Windows binaries: r-devel: discretecdAlgorithm_0.0.7.zip, r-release: discretecdAlgorithm_0.0.7.zip, r-oldrel: discretecdAlgorithm_0.0.7.zip
macOS binaries: r-release (arm64): discretecdAlgorithm_0.0.7.tgz, r-oldrel (arm64): discretecdAlgorithm_0.0.7.tgz, r-release (x86_64): discretecdAlgorithm_0.0.7.tgz
Old sources: discretecdAlgorithm archive


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