{
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  "Package": "clustrd",
  "Type": "Package",
  "Title": "Methods for Joint Dimension Reduction and Clustering",
  "Description": "A class of methods that combine dimension reduction and\nclustering of continuous, categorical or mixed-type data\n(Markos, Iodice D'Enza and van de Velden 2019;\n<DOI:10.18637/jss.v091.i10>). For continuous data, the package\ncontains implementations of factorial K-means (Vichi and Kiers\n2001; <DOI:10.1016/S0167-9473(00)00064-5>) and reduced K-means\n(De Soete and Carroll 1994;\n<DOI:10.1007/978-3-642-51175-2_24>); both methods that combine\nprincipal component analysis with K-means clustering. For\ncategorical data, the package provides MCA K-means (Hwang,\nDillon and Takane 2006; <DOI:10.1007/s11336-004-1173-x>), i-FCB\n(Iodice D'Enza and Palumbo 2013,\n<DOI:10.1007/s00180-012-0329-x>) and Cluster Correspondence\nAnalysis (van de Velden, Iodice D'Enza and Palumbo 2017;\n<DOI:10.1007/s11336-016-9514-0>), which combine multiple\ncorrespondence analysis with K-means. For mixed-type data, it\nprovides mixed Reduced K-means and mixed Factorial K-means (van\nde Velden, Iodice D'Enza and Markos 2019;\n<DOI:10.1002/wics.1456>), which combine PCA for mixed-type data\nwith K-means.",
  "Version": "1.4.0",
  "Date": "2022-07-16",
  "Author": "Angelos Markos [aut, cre], Alfonso Iodice D'Enza [aut], Michel\nvan de Velden [aut]",
  "Maintainer": "Angelos Markos <amarkos@gmail.com>",
  "License": "GPL-3",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-31 09:46:09 UTC",
    "User": "root"
  },
  "Config/pak/sysreqs": "libicu-dev libssl-dev",
  "Repository": "https://amarkos.r-universe.dev",
  "Date/Publication": "2022-07-16 22:20:06 UTC",
  "RemoteUrl": "https://github.com/cran/clustrd",
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  "_created": "2026-05-31T09:46:09.000Z",
  "_published": "2026-05-31T09:50:31.156Z",
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      "date": "2013-09-17"
    },
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    "cluspcamix",
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        "Con",
        "Bran",
        "Pun"
      ],
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      "tojson": true
    },
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      ],
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      "title": "Humor Styles",
      "object": "hsq",
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      ],
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      ],
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      "table": true,
      "tojson": true
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      "object": "macro",
      "file": "macro.rda",
      "class": [
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      ],
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        "IR",
        "TB",
        "NNS"
      ],
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      "table": true,
      "tojson": true
    },
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      "title": "James Bond films",
      "object": "mybond",
      "file": "mybond.rda",
      "class": [
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        "rtime",
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        "actor",
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      ],
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      "table": true,
      "tojson": true
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  "_help": [
    {
      "page": "clustrd",
      "title": "Methods for Joint Dimension Reduction and Clustering",
      "topics": [
        "clustrd-package",
        "clustrd"
      ]
    },
    {
      "page": "bribery",
      "title": "Bribery cases in Russia",
      "topics": [
        "bribery"
      ]
    },
    {
      "page": "clusmca",
      "title": "Joint dimension reduction and clustering of categorical data.",
      "topics": [
        "clusmca",
        "fitted.clusmca",
        "print.clusmca",
        "summary.clusmca"
      ]
    },
    {
      "page": "cluspca",
      "title": "Joint dimension reduction and clustering of continuous data.",
      "topics": [
        "cluspca",
        "fitted.cluspca",
        "print.cluspca",
        "summary.cluspca"
      ]
    },
    {
      "page": "cluspcamix",
      "title": "Joint dimension reduction and clustering of mixed-type data.",
      "topics": [
        "cluspcamix",
        "fitted.cluspcamix",
        "print.cluspcamix",
        "summary.cluspcamix"
      ]
    },
    {
      "page": "cmc",
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      "topics": [
        "cmc"
      ]
    },
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      "page": "diamond",
      "title": "Diamond Stone Pricing",
      "topics": [
        "diamond"
      ]
    },
    {
      "page": "global_bootclus",
      "title": "Global stabiliy assessment of Joint Dimension Reduction and Clustering methods by bootstrapping.",
      "topics": [
        "global_bootclus"
      ]
    },
    {
      "page": "hsq",
      "title": "Humor Styles",
      "topics": [
        "hsq"
      ]
    },
    {
      "page": "local_bootclus",
      "title": "Cluster-wise stability assessment of Joint Dimension Reduction and Clustering methods by bootstrapping.",
      "topics": [
        "local_bootclus"
      ]
    },
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      "title": "Economic Indicators of 20 OECD countries for 1999",
      "topics": [
        "macro"
      ]
    },
    {
      "page": "mybond",
      "title": "James Bond films",
      "topics": [
        "mybond"
      ]
    },
    {
      "page": "plot.clusmca",
      "title": "Plotting function for 'clusmca()' output.",
      "topics": [
        "plot.clusmca"
      ]
    },
    {
      "page": "plot.cluspca",
      "title": "Plotting function for 'cluspca()' output.",
      "topics": [
        "plot.cluspca"
      ]
    },
    {
      "page": "plot.cluspcamix",
      "title": "Plotting function for 'cluspcamix()' output.",
      "topics": [
        "plot.cluspcamix"
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    },
    {
      "page": "tuneclus",
      "title": "Cluster quality assessment for a range of clusters and dimensions.",
      "topics": [
        "fitted.tuneclus",
        "print.tuneclus",
        "summary.tuneclus",
        "tuneclus"
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