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Bayesian network structure learning, parameter learning and inference. This package implements constraint-based (PC, GS, IAMB, Inter-IAMB, Fast-IAMB, MMPC, Hiton-PC, HPC), pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing and Tabu Search) and hybrid (MMHC, RSMAX2, H2PC) structure learning algorithms for discrete, Gaussian and conditional Gaussian networks, along with many score functions and conditional independence tests. The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are also implemented. Some utility functions (model comparison and manipulation, random data generation, arc orientation testing, simple and advanced plots) are included, as well as support for parameter estimation (maximum likelihood and Bayesian) and inference, conditional probability queries, cross-validation, bootstrap and model averaging. Development snapshots with the latest bugfixes are available from <https://www.bnlearn.com/>.
Version: | 5.0 |
Depends: | R (≥ 4.4.0), methods |
Suggests: | parallel, graph, Rgraphviz, igraph, lattice, gRbase, gRain (≥ 1.3-3), Rmpfr, gmp |
Published: | 2024-07-30 |
DOI: | 10.32614/CRAN.package.bnlearn |
Author: | Marco Scutari [aut, cre], Tomi Silander [ctb] |
Maintainer: | Marco Scutari <scutari at bnlearn.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://www.bnlearn.com/ |
NeedsCompilation: | yes |
SystemRequirements: | USE_C17 |
Citation: | bnlearn citation info |
Materials: | ChangeLog |
In views: | Bayesian, GraphicalModels, HighPerformanceComputing |
CRAN checks: | bnlearn results |
Reference manual: | bnlearn.pdf |
Package source: | bnlearn_5.0.tar.gz |
Windows binaries: | r-devel: bnlearn_5.0.zip, r-release: bnlearn_5.0.zip, r-oldrel: bnlearn_4.9.4.zip |
macOS binaries: | r-release (arm64): bnlearn_4.9.4.tgz, r-oldrel (arm64): bnlearn_4.9.4.tgz, r-release (x86_64): bnlearn_5.0.tgz, r-oldrel (x86_64): bnlearn_4.9.4.tgz |
Old sources: | bnlearn archive |
Reverse depends: | BNSL, dbnR, GroupBN |
Reverse imports: | BayesianNetwork, BayesNetBP, bayesvl, bnmonitor, bnpa, BNrich, bnviewer, CBNplot, criticality, dbnlearn, GmicR, imbalance, mDAG, MetNet, MoTBFs, MRPC, OrdCD, pchc, Pigengene, PROPS, r.blip, rPACI, SELF, StratifiedBalancing, TRONCO |
Reverse suggests: | CompareCausalNetworks, ggkegg, OGI, ParallelPC, rbmn, stagedtrees |
Please use the canonical form https://CRAN.R-project.org/package=bnlearn to link to this page.
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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