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mDAG: Inferring Causal Network from Mixed Observational Data Using a Directed Acyclic Graph

Learning a mixed directed acyclic graph based on both continuous and categorical data.

Version: 1.2.2
Depends: R (≥ 2.10), logistf
Imports: Rcpp (≥ 0.12.14), pcalg, mgm, bnlearn, methods, nnet
LinkingTo: Rcpp, RcppArmadillo
Published: 2019-08-20
Author: Wujuan Zhong, Li Dong, Quefeng Li, Xiaojing Zheng
Maintainer: Wujuan Zhong <zhongwujuan at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: mDAG results

Documentation:

Reference manual: mDAG.pdf

Downloads:

Package source: mDAG_1.2.2.tar.gz
Windows binaries: r-devel: mDAG_1.2.2.zip, r-release: mDAG_1.2.2.zip, r-oldrel: mDAG_1.2.2.zip
macOS binaries: r-release (arm64): mDAG_1.2.2.tgz, r-oldrel (arm64): mDAG_1.2.2.tgz, r-release (x86_64): mDAG_1.2.2.tgz, r-oldrel (x86_64): mDAG_1.2.2.tgz
Old sources: mDAG archive

Linking:

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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.
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