Package: pchc
Type: Package
Title: Bayesian Network Learning with the PCHC and Related Algorithms
Version: 1.4
Date: 2026-03-25
Authors@R: c(person("Michail", "Tsagris", role = c("aut", "cre"), email = "mtsagris@uoc.gr"))
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: bigstatsr, bnlearn, dcov, foreach, doParallel, parallel,
        rangen, Rfast, Rfast2, robustbase, stats
Suggests: bigreadr, Rgraphviz
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>.
			 c) Sevinc V. and Tsagris M. (2024). "On the Hyperparameters of PCTABU and PCHC Bayesian Network Learning Algorithms". <doi:10.21203/rs.3.rs-5137132/v1>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-03-25 20:07:05 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-03-25 22:20:08 UTC
Built: R 4.6.0; ; 2026-04-26 14:25:37 UTC; unix
