{
  "_id": "6a0fed92acfb0bcc41c73f37",
  "Package": "mixsmsn",
  "Title": "Fitting Finite Mixture of Scale Mixture of Skew-Normal\nDistributions",
  "Version": "1.1-12",
  "Authors@R": "c(person(given = \"Marcos\",family = \"Prates\", role=c(\"aut\",\"cre\",\"trl\"),\nemail=\"marcosop@est.ufmg.br\", comment = c(ORCID = \"0000-0001-8077-4898\")),\nperson(given = \"Victor\",family=\"Lachos\", role=\"aut\", comment = c(ORCID = \"0000-0002-7239-2459\")),\nperson(given = \"Celso\",family=\"Cabral\", role=\"aut\"))",
  "Description": "Functions to fit finite mixture of scale mixture of\nskew-normal (FM-SMSN) distributions, details in Prates, Lachos\nand Cabral (2013) <doi: 10.18637/jss.v054.i12>, Cabral, Lachos\nand Prates (2012) <doi:10.1016/j.csda.2011.06.026> and Basso,\nLachos, Cabral and Ghosh (2010)\n<doi:10.1016/j.csda.2009.09.031>.",
  "Author": "Marcos Prates [aut, cre, trl] (ORCID:\n<https://orcid.org/0000-0001-8077-4898>), Victor Lachos [aut]\n(ORCID: <https://orcid.org/0000-0002-7239-2459>), Celso Cabral\n[aut]",
  "Maintainer": "Marcos Prates <marcosop@est.ufmg.br>",
  "License": "GPL (>= 2.0)",
  "Packaged": {
    "Date": "2026-05-22 05:43:18 UTC",
    "User": "root"
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  "NeedsCompilation": "no",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-01-21 13:40:02 UTC",
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    "author": "Marcos Prates <marcosop@est.ufmg.br>",
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    "message": "version 1.1-12\n",
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    "email": "marcosop@est.ufmg.br",
    "orcid": "0000-0001-8077-4898"
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      "date": "2015-09-15"
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      "date": "2017-07-17"
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      "date": "2020-04-17"
    },
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      "date": "2021-05-12"
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      "date": "2025-04-23"
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  "_exports": [
    "im.smsn",
    "imm.smsn",
    "mix.contour",
    "mix.dens",
    "mix.hist",
    "mix.lines",
    "mix.print",
    "rmix",
    "rmmix",
    "smsn.mix",
    "smsn.mmix",
    "smsn.search"
  ],
  "_datasets": [
    {
      "name": "bmi",
      "title": "Body Mass Index",
      "object": "bmi",
      "file": "bmi.txt.gz",
      "class": [
        "data.frame"
      ],
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        "bmi"
      ],
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      "table": true,
      "tojson": true
    },
    {
      "name": "faithful",
      "title": "Old Faithful Geyser Data",
      "object": "faithful",
      "file": "faithful.txt.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
        "eruptions",
        "waiting"
      ],
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      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "bmi",
      "title": "Body Mass Index",
      "topics": [
        "bmi"
      ]
    },
    {
      "page": "faithful",
      "title": "Old Faithful Geyser Data",
      "topics": [
        "faithful"
      ]
    },
    {
      "page": "im.smsn",
      "title": "Information matrix",
      "topics": [
        "im.smsn"
      ]
    },
    {
      "page": "imm.smsn",
      "title": "Information matrix",
      "topics": [
        "imm.smsn"
      ]
    },
    {
      "page": "mix.contour",
      "title": "Print the selected groups with contours",
      "topics": [
        "mix.contour"
      ]
    },
    {
      "page": "mix.dens",
      "title": "Estimated densities",
      "topics": [
        "mix.dens"
      ]
    },
    {
      "page": "mix.hist",
      "title": "Estimated densities",
      "topics": [
        "mix.hist"
      ]
    },
    {
      "page": "mix.lines",
      "title": "Plot lines of smsn densities",
      "topics": [
        "mix.lines"
      ]
    },
    {
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      "title": "Printing mix object",
      "topics": [
        "mix.print"
      ]
    },
    {
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      "title": "Random univariate FM-SMSN generator",
      "topics": [
        "rmix"
      ]
    },
    {
      "page": "rmmix",
      "title": "Random multivariate FM-SMSN generator",
      "topics": [
        "rmmix"
      ]
    },
    {
      "page": "smsn.mix",
      "title": "Fit univariate FM-SMSN distribution",
      "topics": [
        "smsn.mix"
      ]
    },
    {
      "page": "smsn.mmix",
      "title": "Fit multivariate FM-SMSN distributions.",
      "topics": [
        "smsn.mmix"
      ]
    },
    {
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      "title": "Find the best number of cluster for a determined data set.",
      "topics": [
        "smsn.search"
      ]
    }
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