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>.

Package details

AuthorMichail Tsagris [aut, cre]
MaintainerMichail Tsagris <mtsagris@uoc.gr>
LicenseGPL (>= 2)
Version1.3
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("pchc")

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pchc documentation built on April 4, 2025, 1:11 a.m.