bnstruct: Bayesian Network Structure Learning from Data with Missing Values

Bayesian Network Structure Learning from Data with Missing Values. The package implements the Silander-Myllymaki complete search, the Max-Min Parents-and-Children, the Hill-Climbing, the Max-Min Hill-climbing heuristic searches, and the Structural Expectation-Maximization algorithm. Available scoring functions are BDeu, AIC, BIC. The package also implements methods for generating and using bootstrap samples, imputed data, inference.

Version:	1.0.15
Depends:	R (≥ 3.5.0), bitops, igraph, methods
Suggests:	graph, Rgraphviz, qgraph, knitr, testthat
Published:	2024-01-09
Author:	Francesco Sambo [aut], Alberto Franzin [aut, cre]
Maintainer:	Alberto Franzin <afranzin at ulb.ac.be>
License:	GPL-2 | GPL-3 | file LICENSE [expanded from: GPL (≥ 2) | file LICENSE]
NeedsCompilation:	yes
Citation:	bnstruct citation info
Materials:	README NEWS
In views:	GraphicalModels, MissingData
CRAN checks:	bnstruct results

Documentation:

Reference manual:	bnstruct.pdf
Vignettes:	\texttt{bnstruct}: an R package for Bayesian Network Structure Learning

Downloads:

Package source:	bnstruct_1.0.15.tar.gz
Windows binaries:	r-devel: bnstruct_1.0.15.zip, r-release: bnstruct_1.0.15.zip, r-oldrel: bnstruct_1.0.15.zip
macOS binaries:	r-release (arm64): bnstruct_1.0.15.tgz, r-oldrel (arm64): bnstruct_1.0.15.tgz, r-release (x86_64): bnstruct_1.0.15.tgz, r-oldrel (x86_64): bnstruct_1.0.15.tgz
Old sources:	bnstruct archive

Reverse dependencies:

Reverse imports:	DExMA, IntOMICS, NIMAA, TGS
Reverse suggests:	BoltzMM

Linking:

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