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: 2026-07-16 05:46:19 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2026-03-25 23:54:10 UTC
RemoteUrl: https://github.com/cran/pchc
RemoteRef: HEAD
RemoteSha: cadd7138bebfc5dbc59089e74c01d0f4b4aabffa