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pchc: Bayesian Network Learning with the PCHC and Related Algorithms

Bayesian network learning using the PCHC, FEDHC, MMHC and variants of these algorithms. PCHC stands for PC Hill-Climbing, a new hybrid algorithm that uses PC to construct the skeleton of the BN and then applies the Hill-Climbing greedy search. More algorithms and variants have been added, such as MMHC, FEDHC, and the Tabu search variants, PCTABU, MMTABU and FEDTABU. The relevant papers are: a) Tsagris M. (2021). "A new scalable Bayesian network learning algorithm with applications to economics". Computational Economics, 57(1): 341-367. <doi:10.1007/s10614-020-10065-7>. b) Tsagris M. (2022). "The FEDHC Bayesian Network Learning Algorithm". Mathematics 2022, 10(15): 2604. <doi:10.3390/math10152604>.

Version: 1.3
Depends: R (≥ 4.0)
Imports: bigstatsr, bnlearn, dcov, foreach, doParallel, parallel, Rfast, Rfast2, robustbase, stats
Suggests: bigreadr, Rgraphviz
Published: 2024-12-06
DOI: 10.32614/CRAN.package.pchc
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris at uoc.gr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: GraphicalModels
CRAN checks: pchc results

Documentation:

Reference manual: pchc.pdf

Downloads:

Package source: pchc_1.3.tar.gz
Windows binaries: r-devel: pchc_1.3.zip, r-release: pchc_1.3.zip, r-oldrel: pchc_1.3.zip
macOS binaries: r-release (arm64): pchc_1.3.tgz, r-oldrel (arm64): pchc_1.3.tgz, r-release (x86_64): pchc_1.3.tgz, r-oldrel (x86_64): pchc_1.3.tgz
Old sources: pchc archive

Linking:

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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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