{
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  "Package": "CensMFM",
  "Type": "Package",
  "Title": "Finite Mixture of Multivariate Censored/Missing Data",
  "Version": "3.1",
  "Date": "2024-05-13",
  "Authors@R": "c(\nperson(\"Francisco H. C.\", \"de Alencar\", email = \"hildemardealencar@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"Christian E.\", \"Galarza\", email = \"cgalarza88@gmail.com\", role = \"aut\"),\nperson(\"Larissa A.\", \"Matos\", email = \"larissa.amatos@gmail.com\", role = \"ctb\"),\nperson(\"Victor H.\", \"Lachos\", email = \"hlachos@gmail.com\", role = \"ctb\"))",
  "Description": "It fits finite mixture models for censored or/and missing\ndata using several multivariate distributions. Point estimation\nand asymptotic inference (via empirical information matrix) are\noffered as well as censored data generation. Pairwise scatter\nand contour plots can be generated. Possible multivariate\ndistributions are the well-known normal, Student-t and\nskew-normal distributions. This package is an complement of\nLachos, V. H., Moreno, E. J. L., Chen, K. & Cabral, C. R. B.\n(2017) <doi:10.1016/j.jmva.2017.05.005> for the multivariate\nskew-normal case.",
  "License": "GPL (>= 2)",
  "Encoding": "UTF-8",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-12 09:22:51 UTC",
    "User": "root"
  },
  "Author": "Francisco H. C. de Alencar [aut, cre], Christian E. Galarza\n[aut], Larissa A. Matos [ctb], Victor H. Lachos [ctb]",
  "Maintainer": "Francisco H. C. de Alencar <hildemardealencar@gmail.com>",
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  "Repository": "https://franciscoalencar.r-universe.dev",
  "Date/Publication": "2024-05-15 02:40:27 UTC",
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      "page": "CensMFM-package",
      "title": "Finite Mixture of Multivariate Censored/Missing Data",
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        "CensMFM"
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      "page": "fit.FMMSNC",
      "title": "Fitting Finite Mixture of Multivariate Distributions.",
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        "fit.FMMSNC"
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      "title": "Random Generator of Finite Mixture of Multivariate Distributions.",
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        "rMMSN"
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      ]
    },
    {
      "page": "rMSN",
      "title": "Generating from Multivariate Skew-normal and Normal Random Distributions.",
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