{ "_id": "6a1f0d48b401979e7341cfe5", "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 ", "Description": "Bayesian network learning using the PCHC, FEDHC, MMHC and\nvariants of these algorithms. PCHC stands for PC Hill-Climbing,\na new hybrid algorithm that uses PC to construct the skeleton\nof the BN and then applies the Hill-Climbing greedy search.\nMore algorithms and variants have been added, such as MMHC,\nFEDHC, and the Tabu search variants, PCTABU, MMTABU and\nFEDTABU. The relevant papers are: a) Tsagris M. (2021). \"A new\nscalable Bayesian network learning algorithm with applications\nto economics\". Computational Economics, 57(1): 341-367.\n. b) Tsagris M. (2022). \"The\nFEDHC Bayesian Network Learning Algorithm\". Mathematics 2022,\n10(15): 2604. . c) Sevinc V. and\nTsagris M. (2024). \"On the Hyperparameters of PCTABU and PCHC\nBayesian Network Learning Algorithms\".\n.", "License": "GPL (>= 2)", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-17 08:54:59 UTC", "User": "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", "MD5sum": "929243bddec1025a3ee92c230e966783", "_user": "cran", "_type": "src", "_file": "pchc_1.4.tar.gz", "_fileid": "ea3316ab0bf957a6065cecf1ee39343c2dc7af2be0fb49c8803bef5f7a1ba45a", "_filesize": 342845, "_sha256": "ea3316ab0bf957a6065cecf1ee39343c2dc7af2be0fb49c8803bef5f7a1ba45a", "_created": "2026-05-17T08:54:59.000Z", "_published": "2026-06-02T17:05:12.807Z", "_distro": "noble", "_jobs": [ { "job": 79127506976, "time": 147, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7041014261" }, { "job": 79127507355, "time": 146, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7041013999" }, { "job": 79127505988, "time": 194, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7040996726" }, { "job": 79127505896, "time": 136, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7364583509" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/25986349549", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/pchc", "_commit": { "id": "cadd7138bebfc5dbc59089e74c01d0f4b4aabffa", "author": "Michail Tsagris ", "committer": "cran-robot ", "message": "version 1.4\n", "time": 1774482850 }, "_maintainer": { "name": "Michail Tsagris", "email": "mtsagris@uoc.gr" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.0", "role": "Depends" }, { "package": "bigstatsr", "role": "Imports" }, { "package": "bnlearn", "role": "Imports" }, { "package": "dcov", "role": "Imports" }, { "package": "foreach", "role": "Imports" }, { "package": "doParallel", "role": "Imports" }, { "package": "parallel", "role": "Imports" }, { "package": "rangen", "role": "Imports" }, { "package": "Rfast", "role": "Imports" }, { "package": "Rfast2", "role": "Imports" }, { "package": "robustbase", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "bigreadr", "role": "Suggests" }, { "package": "Rgraphviz", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [ { "week": "2026-13", "n": 1 } ], "_tags": [ { "name": "1.4", "date": "2026-03-25" } ], "_stars": 0, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 342, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/pchc" }, "_searchresults": 7, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/pchc.html", "manual.pdf" ], "_realowner": "cran", "_cranurl": false, "_releases": [ { "version": "0.1", "date": "2020-07-06" }, { "version": "0.2", "date": "2020-08-28" }, { "version": "0.3", "date": "2020-11-30" }, { "version": "0.4", "date": "2021-02-22" }, { "version": "0.5", "date": "2021-03-21" }, { "version": "0.6", "date": "2021-10-15" }, { "version": "0.7", "date": "2022-02-14" }, { "version": "0.8", "date": "2022-06-18" }, { "version": "0.9", "date": "2023-03-22" }, { "version": "1.0", "date": "2023-03-27" }, { "version": "1.1", "date": "2023-08-09" }, { "version": "1.2", "date": "2023-09-06" }, { "version": "1.3", "date": "2024-12-06" }, { "version": "1.4", "date": "2026-03-25" } ], "_exports": [ "auc", "big_cor", "big_read", "bn.skel.utils", "bn.skel.utils2", "bnmat", "bnplot", "cat.tests", "chi2test", "chi2test_univariate", "conf.edge.lower", "cor.fbed", "cor2pcor", "corpairs", "correls", "cortest", "dcor.fedhc.skel", "dcor.mmhc.skel", "fedhc", "fedhc.boot", "fedhc.skel", "fedhc.skel.boot", "fedtabu", "fedtabu.boot", "g2test", "g2test_perm", "g2test_univariate", "g2test_univariate_perm", "is.dag", "mb", "mmhc", "mmhc.boot", "mmhc.skel", "mmhc.skel.boot", "mmpc", "mmtabu", "mmtabu.boot", "pc.sel", "pchc", "pchc.boot", "pchc.skel", "pchc.skel.boot", "pcor", "pctabu", "pctabu.boot", "pi0est", "rbn", "rbn2", "rbn3", "rmcd", "topological_sort" ], "_help": [ { "page": "pchc-package", "title": "Bayesian Network Learning with the PCHC and Related Algorithms", "topics": [ "pchc-package" ] }, { "page": "bnmat", "title": "Adjacency matrix of a Bayesian network", "topics": [ "bnmat" ] }, { "page": "g2test_univariate", "title": "All pairwise G-square and chi-square tests of indepedence", "topics": [ "chi2test_univariate", "g2test_univariate", "g2test_univariate_perm" ] }, { "page": "pchc.skel.boot", "title": "Bootstrap versions of the skeleton of a Bayesian network", "topics": [ "fedhc.skel.boot", "mmhc.skel.boot", "pchc.skel.boot" ] }, { "page": "fedhc.boot", "title": "Bootstrapping the FEDHC and FEDTABU Bayesian network learning algorithms", "topics": [ "fedhc.boot", "fedtabu.boot" ] }, { "page": "mmhc.boot", "title": "Bootstrapping the MMHC and MMTABU Bayesian network learning algorithms", "topics": [ "mmhc.boot", "mmtabu.boot" ] }, { "page": "pchc.boot", "title": "Bootstrapping the PCHC and PCTABU Bayesian network learning algorithms", "topics": [ "pchc.boot", "pctabu.boot" ] }, { "page": "is.dag", "title": "Check whether a directed graph is acyclic", "topics": [ "is.dag" ] }, { "page": "cat.tests", "title": "Chi-square and G-square tests of (unconditional) indepdence", "topics": [ "cat.tests" ] }, { "page": "rbn2", "title": "Continuous data simulation from a DAG.", "topics": [ "rbn2", "rbn3" ] }, { "page": "corpairs", "title": "Correlation between pairs of variables", "topics": [ "corpairs" ] }, { "page": "big_cor", "title": "Correlation matrix for FBM class matrices (big matrices)", "topics": [ "big_cor" ] }, { "page": "cortest", "title": "Correlation significance testing using Fisher's z-transformation", "topics": [ "cortest" ] }, { "page": "correls", "title": "Correlation between a vector and a set of variables", "topics": [ "correls" ] }, { "page": "pi0est", "title": "Estimation of the percentage of null p-values", "topics": [ "pi0est" ] }, { "page": "g2test", "title": "G-square test of conditional indepdence", "topics": [ "chi2test", "g2test", "g2test_perm" ] }, { "page": "conf.edge.lower", "title": "Lower limit of the confidence of an edge", "topics": [ "conf.edge.lower" ] }, { "page": "mb", "title": "Markov blanket of a node in a Bayesian network", "topics": [ "mb" ] }, { "page": "rmcd", "title": "Outliers free data via the reweighted MCD", "topics": [ "rmcd" ] }, { "page": "pcor", "title": "Partial correlation", "topics": [ "pcor" ] }, { "page": "cor2pcor", "title": "Partial correlation matrix from correlation or covariance matrix", "topics": [ "cor2pcor" ] }, { "page": "bnplot", "title": "Plot of a Bayesian network", "topics": [ "bnplot" ] }, { "page": "rbn", "title": "Random values simulation from a Bayesian network", "topics": [ "rbn" ] }, { "page": "big_read", "title": "Read big data or a big.matrix object", "topics": [ "big_read" ] }, { "page": "auc", "title": "ROC and AUC", "topics": [ "auc" ] }, { "page": "dcor.fedhc.skel", "title": "The skeleton of a Bayesian network produced by the MMHC or the FEDHC algorithm using the distance correlation", "topics": [ "dcor.fedhc.skel", "dcor.mmhc.skel" ] }, { "page": "fedhc.skel", "title": "The skeleton of a Bayesian network produced by the FEDHC algorithm", "topics": [ "fedhc.skel" ] }, { "page": "mmhc.skel", "title": "The skeleton of a Bayesian network learned with the MMHC algorithm", "topics": [ "mmhc.skel" ] }, { "page": "pchc.skel", "title": "The skeleton of a Bayesian network learned with the PC algorithm", "topics": [ "pchc.skel" ] }, { "page": "fedhc", "title": "The FEDHC and FEDTABU Bayesian network learning algorithms", "topics": [ "fedhc", "fedtabu" ] }, { "page": "mmhc", "title": "The MMHC and MMTABU Bayesian network learning algorithms", "topics": [ "mmhc", "mmtabu" ] }, { "page": "pchc", "title": "The PCHC and PCTABU Bayesian network learning algorithms", "topics": [ "pchc", "pctabu" ] }, { "page": "topological_sort", "title": "Topological sort of a Bayesian network", "topics": [ "topological_sort" ] }, { "page": "bn.skel.utils", "title": "Utilities for the skeleton of a (Bayesian) Network", "topics": [ "bn.skel.utils", "bn.skel.utils2" ] }, { "page": "cor.fbed", "title": "Variable selection for continuous data using the FBED algorithm", "topics": [ "cor.fbed" ] }, { "page": "mmpc", "title": "Variable selection for continuous data using the MMPC algorithm", "topics": [ "mmpc" ] }, { "page": "pc.sel", "title": "Variable selection for continuous data using the PC-simple algorithm", "topics": [ "pc.sel" ] } ], "_rundeps": [ "BH", "bigassertr", "bigparallelr", "bigstatsr", "bit", "bnlearn", "cli", "codetools", "cowplot", "cpp11", "dcov", "DEoptimR", "doParallel", "farver", "ff", "flock", "foreach", "ggplot2", "glue", "gtable", "isoband", "iterators", "labeling", "lattice", "lifecycle", "magrittr", "Matrix", "parallelly", "pillar", "pkgconfig", "ps", "R6", "rangen", "RColorBrewer", "Rcpp", "RcppArmadillo", "RcppEigen", "RcppParallel", "Rfast", "Rfast2", "RhpcBLASctl", "rlang", "rmio", "Rnanoflann", "robustbase", "RSpectra", "S7", "scales", "tibble", "utf8", "vctrs", "viridisLite", "withr", "zigg" ], "_score": 1, "_indexed": true, "_nocasepkg": "pchc", "_universes": [ "cran" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.4", "date": "2026-05-17T08:57:14.000Z", "distro": "noble", "commit": "cadd7138bebfc5dbc59089e74c01d0f4b4aabffa", "fileid": "b8d4c34aaf18b3ba4c8543388b7e5c741737632f0873acec435d878e3f02b382", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/25986349549" }, { "r": "4.6.0", "os": "linux", "version": "1.4", "date": "2026-05-17T08:57:07.000Z", "distro": "noble", "commit": "cadd7138bebfc5dbc59089e74c01d0f4b4aabffa", "fileid": "ac58e2d65e854d6b67b68be21cff920af32ec648728f8f1ae6dcbb4533eb3678", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/25986349549" }, { "r": "4.6.0", "os": "wasm", "version": "1.4", "date": "2026-06-02T17:04:45.000Z", "commit": "cadd7138bebfc5dbc59089e74c01d0f4b4aabffa", "fileid": "b1556b99fb219848ea9e649bddc05ffc386f522b9796224d9934e22b1ba107dd", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/25986349549" } ] }