{ "_id": "6a1f1c56b401979e7341f74d", "Package": "biplotEZ", "Title": "EZ-to-Use Biplots", "Version": "2.3", "Authors@R": "c(person(\"Sugnet\", \"Lubbe\", , \"muvisu@sun.ac.za\", role = c(\"aut\", \"cre\",\"cph\"),\ncomment = c(ORCID = \"0000-0003-2762-9944\")),\nperson(\"Niël\", \"le Roux\", , role = \"aut\",\ncomment = c(ORCID = \"0000-0002-1791-746X\")),\nperson(\"Johané\", \"Nienkemper-Swanepoel\", , role = \"aut\",\ncomment = c(ORCID = \"0000-0001-6086-8272\")),\nperson(\"Raeesa\", \"Ganey\", , role = \"aut\",\ncomment = c(ORCID = \"0009-0008-6973-0999\")),\nperson(\"Ruan\", \"Buys\", , role = \"aut\",\ncomment = c(ORCID = \"0000-0001-8527-8631\")),\nperson(\"Zoë-Mae\", \"Adams\", , role=\"aut\",\ncomment = c(ORCID = \"0000-0003-3730-4887\")),\nperson(\"Peter\", \"Manefeldt\", , role=\"aut\",\ncomment = c(ORCID = \"0000-0002-8604-843X\")))", "Description": "Provides users with an EZ-to-use platform for representing\ndata with biplots. Currently principal component analysis\n(PCA), canonical variate analysis (CVA) and simple\ncorrespondence analysis (CA) biplots are included. This is\naccompanied by various formatting options for the samples and\naxes. Alpha-bags and concentration ellipses are included for\nvisual enhancements and interpretation. For an extensive\ndiscussion on the topic, see Gower, J.C., Lubbe, S. and le\nRoux, N.J. (2011, ISBN: 978-0-470-01255-0) Understanding\nBiplots. Wiley: Chichester.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "NeedsCompilation": "yes", "Repository": "https://muvisu.r-universe.dev", "Date/Publication": "2026-04-16 12:39:54 UTC", "RemoteUrl": "https://github.com/muvisu/biplotez", "RemoteRef": "HEAD", "RemoteSha": "4db8ccf37095dab2d239f731b746f7195721d1aa", "Packaged": { "Date": "2026-05-16 08:59:03 UTC", "User": "root" }, "Author": "Sugnet Lubbe [aut, cre, cph] (ORCID:\n),\nNiël le Roux [aut] (ORCID: ),\nJohané Nienkemper-Swanepoel [aut] (ORCID:\n),\nRaeesa Ganey [aut] (ORCID: ),\nRuan Buys [aut] (ORCID: ),\nZoë-Mae Adams [aut] (ORCID: ),\nPeter Manefeldt [aut] (ORCID: )", "Maintainer": "Sugnet Lubbe ", "MD5sum": "9d1412b3fe265b32ae78b456f300c33f", "_user": "muvisu", "_type": "src", "_file": "biplotEZ_2.3.tar.gz", "_fileid": "9c349b6155014d6faf2d3ad0ac80d2aa46e058da3cfbd7a2e4bc117174f6dce9", 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create a new biplot with 'biplotEZ'", "topics": [ "biplot" ] }, { "page": "biplotEZ", "title": "biplotEZ: EZ-to-Use Biplots", "topics": [ "biplotEZ" ] }, { "page": "CA", "title": "Correspondence Analysis (CA) method", "topics": [ "CA" ] }, { "page": "CA.biplot", "title": "CA biplot", "topics": [ "CA.biplot" ] }, { "page": "CatPCA", "title": "Perform Categorical Principal Components Analysis (CatPCA)", "topics": [ "CatPCA" ] }, { "page": "CatPCA.biplot", "title": "Calculate elements for the CatPCA biplot", "topics": [ "CatPCA.biplot" ] }, { "page": "classification", "title": "Classification biplot method", "topics": [ "classification" ] }, { "page": "classification.biplot", "title": "classification biplot", "topics": [ "classification.biplot" ] }, { "page": "classify", "title": "Classify samples into classes", "topics": [ "classify" ] }, { "page": "CLPs", "title": "Format aesthetics for the category level points", "topics": [ "CLPs" ] }, { "page": "CLRs", "title": "Format aesthetics for the category level regions", "topics": [ "CLRs" ] }, { "page": "CVA", "title": "Perform Canonical Variate Analysis (CVA)", "topics": [ "CVA" ] }, { "page": "CVA.biplot", "title": "Calculate elements for the CVA biplot", "topics": [ "CVA.biplot" ] }, { "page": "CVAlowdim", "title": "Construct additional dimensions when the dimension of the canonical space is smaller than the dimension of the biplot", "topics": [ "CVAlowdim" ] }, { "page": "density1D", "title": "Creates a kernel density in 1-dimension", "topics": [ "density1D" ] }, { "page": "density2D", "title": "Create a density in 2-dimensions", "topics": [ "density2D" ] }, { "page": "ellipses", "title": "Concentration ellipses (kappa-ellipses)", "topics": [ "ellipses" ] }, { "page": "extended.matching.coefficient", "title": "Extended matching coefficient", "topics": [ "extended.matching.coefficient" ] }, { "page": "fit.measures", "title": "Compute measures of fit for the biplot.", "topics": [ "fit.measures" ] }, { "page": "interpolate", "title": "Interpolate supplementary points and variables to add to the biplot", "topics": [ "interpolate" ] }, { "page": "legend.type", "title": "Format the legend for the biplot", "topics": [ "legend.type" ] }, { "page": "means", "title": "Format aesthetics for the class or group means", "topics": [ "means" ] }, { "page": "newaxes", "title": "Format aesthetics for the supplementary (new) biplot axes", "topics": [ "newaxes" ] }, { "page": "newsamples", "title": "Format aesthetics for the supplementary (new) biplot samples", "topics": [ "newsamples" ] }, { "page": "nom.axes", "title": "Format aesthetics for the nominal biplot axes", "topics": [ "nom.axes" ] }, { "page": "ord.axes", "title": "Format aesthetics for the ordinal biplot axes", "topics": [ "ord.axes" ] }, { "page": "PCA", "title": "Perform Principal Components Analysis (PCA)", "topics": [ "PCA" ] }, { "page": "PCA.biplot", "title": "Calculate elements for the PCA biplot", "topics": [ "PCA.biplot" ] }, { "page": 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