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pchc  

Bayesian Network Learning with the PCHC and Related Algorithms
View on CRAN: Click here


Download and install pchc package within the R console
Install from CRAN:
install.packages("pchc")

Install from Github:
library("remotes")
install_github("cran/pchc")

Install by package version:
library("remotes")
install_version("pchc", "1.3")



Attach the package and use:
library("pchc")
Maintained by
Michail Tsagris
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-07-06
Latest Update: 2024-12-06
Description:
Bayesian network learning using the PCHC algorithm. 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. . b) Tsagris M. (2022). The FEDHC Bayesian Network Learning Algorithm. Mathematics 2022, 10(15): 2604. .
How to cite:
Michail Tsagris (2020). pchc: Bayesian Network Learning with the PCHC and Related Algorithms. R package version 1.3, https://cran.r-project.org/web/packages/pchc. Accessed 05 Mar. 2026.
Previous versions and publish date:
0.1 (2020-07-06 18:30), 0.2 (2020-08-28 20:30), 0.3 (2020-11-30 12:00), 0.4 (2021-02-22 18:10), 0.5 (2021-03-21 16:50), 0.6 (2021-10-15 23:30), 0.7 (2022-02-14 12:30), 0.8 (2022-06-18 18:10), 0.9 (2023-03-22 14:40), 1.0 (2023-03-27 00:00), 1.1 (2023-08-09 21:10), 1.2 (2023-09-06 18:20)
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Complete documentation for pchc
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