pchc: Bayesian Network Learning with the PCHC and Related Algorithms

Bayesian network learning using the PCHC algorithm. PCHC stands for PC Hill-Climbing. It is a new hybrid algorithm that used PC to construct the skeleton of the BN and then utilizes the Hill-Climbing greedy search. The relevant papers are a) Tsagris M. (2021). "A new scalable Bayesian network learning algorithm with applications to economics". Computational Economics (To appear). <doi:10.1007/s10614-020-10065-7>. b) Tsagris M. (2020). The FEDHC Bayesian network learning algorithm. <arXiv:2012.00113>.

Version: 0.4
Depends: R (≥ 3.6.0)
Imports: bigmemory, bigstatsr, bnlearn, Rfast, Rfast2, robustbase, stats
Published: 2021-02-22
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris at uoc.gr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: pchc results


Reference manual: pchc.pdf
Package source: pchc_0.4.tar.gz
Windows binaries: r-devel: pchc_0.4.zip, r-release: pchc_0.4.zip, r-oldrel: pchc_0.4.zip
macOS binaries: r-release: pchc_0.4.tgz, r-oldrel: pchc_0.3.tgz
Old sources: pchc archive


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