{ "_id": "6a1421f3acfb0bcc41d3ea3b", "Package": "FactoClass", "Version": "1.2.9", "Date": "2024-01-24", "Title": "Combination of Factorial Methods and Cluster Analysis", "Author": "Campo Elias Pardo , Pedro Cesar del Campo\n and Camilo Jose Torres\n, with the contributions from. Ivan Diaz\n, Mauricio Sadinle\n, Jhonathan Medina\n.", "Maintainer": "Campo Elias Pardo ", "Description": "Some functions of 'ade4' and 'stats' are combined in order\nto obtain a partition of the rows of a data table, with columns\nrepresenting variables of scales: quantitative, qualitative or\nfrequency. First, a principal axes method is performed and\nthen, a combination of Ward agglomerative hierarchical\nclassification and K-means is performed, using some of the\nfirst coordinates obtained from the previous principal axes\nmethod. In order to permit different weights of the elements to\nbe clustered, the function 'kmeansW', programmed in C++, is\nincluded. It is a modification of 'kmeans'. Some graphical\nfunctions include the option: 'gg=FALSE'. When 'gg=TRUE', they\nuse the 'ggplot2' and 'ggrepel' packages to avoid the\nsuper-position of the labels.", "License": "GPL (>= 2)", "Encoding": "UTF-8", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-25 10:12:38 UTC", "User": "root" }, "Repository": "https://cepardot.r-universe.dev", "Date/Publication": "2024-02-01 02:34:10 UTC", "RemoteUrl": "https://github.com/cran/FactoClass", "RemoteRef": "HEAD", "RemoteSha": "b5e7166e715d46d2e76c55a166f5c835c5b8534a", "MD5sum": "e54eef6b13347764c0fb0abbdc7ae14c", "_user": "cepardot", "_type": "src", "_file": "FactoClass_1.2.9.tar.gz", "_fileid": "8c26bfcd2cd54b4a8caf9e6c4af9adf40b3122f1b41e7613a09c10bfbfee5afa", "_filesize": 269137, "_sha256": "8c26bfcd2cd54b4a8caf9e6c4af9adf40b3122f1b41e7613a09c10bfbfee5afa", "_created": "2026-05-25T10:12:38.000Z", "_published": "2026-05-25T10:18:27.705Z", "_distro": "noble", "_jobs": [ { "job": 77694307684, "time": 129, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": 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