{
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  "Package": "otrimle",
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  "Title": "Robust Model-Based Clustering",
  "Description": "Performs robust cluster analysis allowing for outliers and\nnoise that cannot be fitted by any cluster. The data are\nmodelled by a mixture of Gaussian distributions and a noise\ncomponent, which is an improper uniform distribution covering\nthe whole Euclidean space. Parameters are estimated by (pseudo)\nmaximum likelihood. This is fitted by a EM-type algorithm. See\nCoretto and Hennig (2016) <doi:10.1080/01621459.2015.1100996>,\nand Coretto and Hennig (2017)\n<https://jmlr.org/papers/v18/16-382.html>.",
  "Version": "2.0",
  "Date": "2021-05-28",
  "Authors@R": "c(person(\"Pietro\", \"Coretto\",\nrole = c(\"aut\", \"cre\"),\nemail = \"pcoretto@unisa.it\",\ncomment = \"Homepage: <https://pietro-coretto.github.io>\"),\nperson(\"Christian\", \"Hennig\",\nrole = c(\"aut\"),\nemail = \"christian.hennig@unibo.it\",\ncomment = \"Homepage:  <https://www.unibo.it/sitoweb/christian.hennig/en>\")\n)",
  "License": "GPL (>= 2)",
  "LazyData": "TRUE",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-06-01 10:24:39 UTC",
    "User": "root"
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  "Author": "Pietro Coretto [aut, cre] (Homepage:\n<https://pietro-coretto.github.io>), Christian Hennig [aut]\n(Homepage: <https://www.unibo.it/sitoweb/christian.hennig/en>)",
  "Maintainer": "Pietro Coretto <pcoretto@unisa.it>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2021-05-29 05:30:02 UTC",
  "RemoteUrl": "https://github.com/cran/otrimle",
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    "name": "cran",
    "description": "Unofficial read-only mirror of all CRAN R packages"
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    "extra/citation.json",
    "extra/citation.txt",
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      "date": "2016-10-07"
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    },
    {
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    "kerndensmeasure",
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    "otrimle",
    "otrimleg",
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    "plot.summary.otrimlesimgdens",
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    "rimle",
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        "Length",
        "Left",
        "Right",
        "Bottom",
        "Top",
        "Diagonal"
      ],
      "rows": 200,
      "table": true,
      "tojson": true
    }
  ],
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      "page": "banknote",
      "title": "Swiss Banknotes Data",
      "topics": [
        "banknote"
      ]
    },
    {
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      "title": "Generates random data from OTRIMLE output model",
      "topics": [
        "generator.otrimle"
      ]
    },
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      "page": "InitClust",
      "title": "Robust Initialization for Model-based Clustering Methods",
      "topics": [
        "InitClust"
      ]
    },
    {
      "page": "kerndenscluster",
      "title": "Aggregated distance to elliptical unimodal density over clusters",
      "topics": [
        "kerndenscluster"
      ]
    },
    {
      "page": "kerndensmeasure",
      "title": "Statistic measuring closeness to symmetric unimodal distribution",
      "topics": [
        "kerndensmeasure"
      ]
    },
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      "page": "kerndensp",
      "title": "Closeness of multivariate distribution to elliptical unimodal distribution",
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    },
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      "title": "Mean and standard deviation of unimodality statistic",
      "topics": [
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        "ksdfun"
      ]
    },
    {
      "page": "otrimle",
      "title": "Optimally Tuned Robust Improper Maximum Likelihood Clustering",
      "topics": [
        "otrimle",
        "print.otrimle"
      ]
    },
    {
      "page": "otrimleg",
      "title": "OTRIMLE for a range of numbers of clusters with density-based cluster quality statistic",
      "topics": [
        "otrimleg"
      ]
    },
    {
      "page": "otrimlesimg",
      "title": "Adequacy approach for number of clusters for OTRIMLE",
      "topics": [
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        "plot.summary.otrimlesimgdens",
        "print.summary.otrimlesimgdens",
        "summary.otrimlesimgdens"
      ]
    },
    {
      "page": "plot.otrimle",
      "title": "Plot Methods for OTRIMLE Objects",
      "topics": [
        "plot.otrimle"
      ]
    },
    {
      "page": "plot.rimle",
      "title": "Plot Methods for RIMLE Objects",
      "topics": [
        "plot.rimle"
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    },
    {
      "page": "rimle",
      "title": "Robust Improper Maximum Likelihood Clustering",
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        "print.rimle",
        "rimle"
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