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: 1.0.2
Depends: R (≥ 2.10), bitops, Matrix, igraph, methods
Suggests: graph, Rgraphviz, knitr, testthat
Published: 2016-12-13
Author: Francesco Sambo [aut, cre], Alberto Franzin [aut]
Maintainer: Francesco Sambo <francesco.sambo at unipd.it>
License: GPL-2 | GPL-3 | file LICENSE [expanded from: GPL (≥ 2) | file LICENSE]
NeedsCompilation: yes
Materials: README
In views: gR
CRAN checks: bnstruct results

Downloads:

Reference manual: bnstruct.pdf
Vignettes: \texttt{bnstruct}: an R package for Bayesian Network Structure Learning
Package source: bnstruct_1.0.2.tar.gz
Windows binaries: r-devel: bnstruct_1.0.2.zip, r-release: bnstruct_1.0.2.zip, r-oldrel: bnstruct_1.0.2.zip
OS X El Capitan binaries: r-release: bnstruct_1.0.2.tgz
OS X Mavericks binaries: r-oldrel: bnstruct_1.0.2.tgz
Old sources: bnstruct archive

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