Package: pchc
Type: Package
Title: Bayesian Network Learning with the PCHC and Related Algorithms
Version: 0.6
URL:
Date: 2021-10-16
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, Rfast, Rfast2, robustbase, stats
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. <doi:10.1007/s10614-020-10065-7>. 
			 b) Tsagris M. (2021). The FEDHC Bayesian network learning algorithm. <arXiv:2012.00113>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2021-10-15 20:57:40 UTC; Michail
Repository: CRAN
Date/Publication: 2021-10-15 21:30:02 UTC
