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: 1.0.6
Depends: R (≥ 3.5.0), bitops, Matrix, igraph, methods
Suggests: graph, Rgraphviz, qgraph, knitr, testthat
Published: 2019-07-09
Author: Francesco Sambo [aut], Alberto Franzin [aut, cre]
Maintainer: Alberto Franzin <afranzin at>
License: GPL-2 | GPL-3 | file LICENSE [expanded from: GPL (≥ 2) | file LICENSE]
NeedsCompilation: yes
Citation: bnstruct citation info
Materials: README NEWS
In views: gR
CRAN checks: bnstruct results


Reference manual: bnstruct.pdf
Vignettes: \texttt{bnstruct}: an R package for Bayesian Network Structure Learning
Package source: bnstruct_1.0.6.tar.gz
Windows binaries: r-devel:, r-devel-gcc8:, r-release:, r-oldrel:
OS X binaries: r-release: bnstruct_1.0.6.tgz, r-oldrel: bnstruct_1.0.6.tgz
Old sources: bnstruct archive

Reverse dependencies:

Reverse imports: TGS
Reverse suggests: BoltzMM


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