gRain: Graphical Independence Networks

Probability propagation in graphical independence networks, also known as Bayesian networks or probabilistic expert systems. Documentation of the package is provided in vignettes included in the package and in the paper by Højsgaard (2012, <doi:10.18637/jss.v046.i10>). See 'citation("gRain")' for details.

Version:	1.3.10
Depends:	R (≥ 3.6.0), methods, gRbase (≥ 1.8.6.6)
Imports:	graph, Rgraphviz, igraph, stats4, magrittr, Rcpp (≥ 0.11.1)
LinkingTo:	Rcpp (≥ 0.11.1), RcppArmadillo, RcppEigen, gRbase
Suggests:	microbenchmark, knitr, testthat (≥ 2.1.0)
Published:	2022-05-09
Author:	Søren Højsgaard
Maintainer:	Søren Højsgaard <sorenh at math.aau.dk>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://people.math.aau.dk/~sorenh/software/gR/
NeedsCompilation:	yes
Citation:	gRain citation info
Materials:	README NEWS ChangeLog
In views:	Bayesian, GraphicalModels
CRAN checks:	gRain results

Documentation:

Reference manual:	gRain.pdf
Vignettes:	grain-intro

Downloads:

Package source:	gRain_1.3.10.tar.gz
Windows binaries:	r-devel: gRain_1.3.10.zip, r-release: gRain_1.3.10.zip, r-oldrel: gRain_1.3.10.zip
macOS binaries:	r-release (arm64): gRain_1.3.10.tgz, r-oldrel (arm64): gRain_1.3.10.tgz, r-release (x86_64): gRain_1.3.10.tgz, r-oldrel (x86_64): gRain_1.3.10.tgz
Old sources:	gRain archive

Reverse dependencies:

Reverse imports:	bnmonitor, bnspatial, GmicR, gRim, RVS
Reverse suggests:	bnclassify, bnlearn

Linking:

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