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    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
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r-pchc 1.4
Propagated dependencies: r-robustbase@0.99-7 r-rfast2@0.1.5.6 r-rfast@2.1.5.2 r-rangen@0.0.1 r-foreach@1.5.2 r-doparallel@1.0.17 r-dcov@0.1.1 r-bnlearn@5.2.1 r-bigstatsr@1.6.2
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pchc
Licenses: GPL 2+
Build system: r
Synopsis: Bayesian Network Learning with the PCHC and Related Algorithms
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>.

Total packages: 1