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pchc

Bayesian Network Learning with the PCHC and Related Algorithms

v1.3 · Dec 6, 2024 · GPL (>= 2)

Description

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>.

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r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
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ERROR r-devel-linux-x86_64-debian-clang

package dependencies

Package required but not available: ‘Rfast2’

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.
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ERROR 13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Mar 9, 2026
ERROR r-devel-linux-x86_64-debian-clang

package dependencies

Package required but not available: ‘Rfast2’

See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’
manual.

Dependency Network

Dependencies Reverse dependencies bigstatsr bnlearn dcov foreach doParallel Rfast Rfast2 robustbase pchc

Version History

new 1.3 Mar 9, 2026