{
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  "Package": "betareg",
  "Version": "3.2-5",
  "Date": "2026-01-30",
  "Title": "Beta Regression",
  "Authors@R": "c(person(given = \"Achim\", family = \"Zeileis\", role = c(\"aut\", \"cre\"), email = \"Achim.Zeileis@R-project.org\", comment = c(ORCID = \"0000-0003-0918-3766\")),\nperson(given = \"Francisco\", family = \"Cribari-Neto\", role = \"aut\", email = \"cribari@ufpe.br\", comment = c(ORCID = \"0000-0002-5909-6698\")),\nperson(given = \"Bettina\", family = \"Grün\", role = \"aut\", email = \"Bettina.Gruen@wu.ac.at\", comment = c(ORCID = \"0000-0001-7265-4773\")),\nperson(given = \"Ioannis\", family = \"Kosmidis\", role = \"aut\", email = \"ioannis.kosmidis@warwick.ac.uk\", comment = c(ORCID = \"0000-0003-1556-0302\")),\nperson(given = c(\"Alexandre\", \"B.\"), family = \"Simas\", role = \"ctb\", comment = \"earlier version by\"),\nperson(given = c(\"Andrea\", \"V.\"), family = \"Rocha\", role = \"ctb\", comment = \"earlier version by\"))",
  "Description": "Beta regression for modeling beta-distributed dependent\nvariables on the open unit interval (0, 1), e.g., rates and\nproportions, see Cribari-Neto and Zeileis (2010)\n<doi:10.18637/jss.v034.i02>. Moreover, extended-support beta\nregression models can accommodate dependent variables with\nboundary observations at 0 and/or 1, see Kosmidis and Zeileis\n(2025) <doi:10.1093/jrsssc/qlaf039>. For the classical beta\nregression model, alternative specifications are provided:\nBias-corrected and bias-reduced estimation, finite mixture\nmodels, and recursive partitioning for beta regression, see\nGrün, Kosmidis, and Zeileis (2012) <doi:10.18637/jss.v048.i11>.",
  "License": "GPL-2 | GPL-3",
  "URL": "https://topmodels.R-Forge.R-project.org/betareg/",
  "BugReports": "https://topmodels.R-Forge.R-project.org/betareg/contact.html",
  "Encoding": "UTF-8",
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  "Repository": "https://zeileis.r-universe.dev",
  "Date/Publication": "2026-01-30 01:32:01 UTC",
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  "Packaged": {
    "Date": "2026-06-24 02:10:47 UTC",
    "User": "root"
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  "Author": "Achim Zeileis [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-0918-3766>),\nFrancisco Cribari-Neto [aut] (ORCID:\n<https://orcid.org/0000-0002-5909-6698>),\nBettina Grün [aut] (ORCID: <https://orcid.org/0000-0001-7265-4773>),\nIoannis Kosmidis [aut] (ORCID: <https://orcid.org/0000-0003-1556-0302>),\nAlexandre B. Simas [ctb] (earlier version by),\nAndrea V. Rocha [ctb] (earlier version by)",
  "Maintainer": "Achim Zeileis <Achim.Zeileis@R-project.org>",
  "MD5sum": "974a7e17c69647f4c042d3fe8a517f5a",
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  "_created": "2026-06-24T02:10:47.000Z",
  "_published": "2026-06-24T02:16:09.007Z",
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    "Beta4",
    "betamix",
    "BetaR",
    "betar_family",
    "betareg",
    "betareg.control",
    "betareg.fit",
    "betatree",
    "clusters",
    "dbeta01",
    "dbeta4",
    "dbetar",
    "dxbeta",
    "dxbetax",
    "extraComponent",
    "fitted",
    "gleverage",
    "pbeta01",
    "pbeta4",
    "pbetar",
    "posterior",
    "predict",
    "pxbeta",
    "pxbetax",
    "qbeta01",
    "qbeta4",
    "qbetar",
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    "qxbetax",
    "rbeta01",
    "rbeta4",
    "rbetar",
    "rxbeta",
    "rxbetax",
    "XBeta",
    "XBetaX",
    "xbetax_family"
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      "title": "Partition-Primed Probability Judgement Task for Car Dealership",
      "object": "CarTask",
      "file": "CarTask.rda",
      "class": [
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      ],
      "fields": [
        "task",
        "probability",
        "NFCCscale"
      ],
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      "table": true,
      "tojson": true
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      "title": "Proportion of Household Income Spent on Food",
      "object": "FoodExpenditure",
      "file": "FoodExpenditure.rda",
      "class": [
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        "income",
        "persons"
      ],
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      "table": true,
      "tojson": true
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      "title": "Estimation of Gasoline Yields from Crude Oil",
      "object": "GasolineYield",
      "file": "GasolineYield.rda",
      "class": [
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        "pressure",
        "temp10",
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        "batch"
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        "location",
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        "male",
        "age",
        "treatment",
        "grade",
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      "object": "MockJurors",
      "file": "MockJurors.rda",
      "class": [
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        "conflict",
        "confidence"
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      "table": true,
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      "title": "Dyslexia and IQ Predicting Reading Accuracy",
      "object": "ReadingSkills",
      "file": "ReadingSkills.rda",
      "class": [
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        "accuracy1"
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      "table": true,
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      "title": "Dependency of Anxiety on Stress",
      "object": "StressAnxiety",
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        "anxiety"
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      "table": true,
      "tojson": true
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    {
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      "title": "Weather Task with Priming and Precise and Imprecise Probabilities",
      "object": "WeatherTask",
      "file": "WeatherTask.rda",
      "class": [
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      "fields": [
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        "eliciting",
        "agreement"
      ],
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      "table": true,
      "tojson": true
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  "_help": [
    {
      "page": "dbeta01",
      "title": "The Zero- and/or One-Inflated Beta Distribution in Regression Parameterization",
      "topics": [
        "dbeta01",
        "pbeta01",
        "qbeta01",
        "rbeta01"
      ]
    },
    {
      "page": "Beta01",
      "title": "Create a Zero- and/or One-Inflated Beta Distribution",
      "topics": [
        "Beta01",
        "cdf.Beta01",
        "is_continuous.Beta01",
        "is_discrete.Beta01",
        "kurtosis.Beta01",
        "log_pdf.Beta01",
        "mean.Beta01",
        "pdf.Beta01",
        "quantile.Beta01",
        "random.Beta01",
        "skewness.Beta01",
        "support.Beta01",
        "variance.Beta01"
      ]
    },
    {
      "page": "dbeta4",
      "title": "The 4-Parameter Beta Distribution in Regression Parameterization",
      "topics": [
        "dbeta4",
        "pbeta4",
        "qbeta4",
        "rbeta4"
      ]
    },
    {
      "page": "Beta4",
      "title": "Create a 4-Parameter Beta Distribution",
      "topics": [
        "Beta4",
        "cdf.Beta4",
        "is_continuous.Beta4",
        "is_discrete.Beta4",
        "kurtosis.Beta4",
        "log_pdf.Beta4",
        "mean.Beta4",
        "pdf.Beta4",
        "quantile.Beta4",
        "random.Beta4",
        "skewness.Beta4",
        "support.Beta4",
        "variance.Beta4"
      ]
    },
    {
      "page": "betamix",
      "title": "Finite Mixtures of Beta Regression for Rates and Proportions",
      "topics": [
        "betamix",
        "clusters,betamix,ANY-method",
        "extraComponent",
        "fitted,betamix-method",
        "fitted,FLXMRbeta-method",
        "posterior,betamix,ANY-method",
        "predict,betamix-method",
        "predict,FLXMRbeta-method",
        "predict,FLXMRbetafix-method"
      ]
    },
    {
      "page": "dbetar",
      "title": "The Beta Distribution in Regression Parameterization",
      "topics": [
        "dbetar",
        "pbetar",
        "qbetar",
        "rbetar"
      ]
    },
    {
      "page": "BetaR",
      "title": "Create a Beta Regression Distribution",
      "topics": [
        "BetaR",
        "cdf.BetaR",
        "is_continuous.BetaR",
        "is_discrete.BetaR",
        "kurtosis.BetaR",
        "log_pdf.BetaR",
        "mean.BetaR",
        "pdf.BetaR",
        "quantile.BetaR",
        "random.BetaR",
        "skewness.BetaR",
        "support.BetaR",
        "variance.BetaR"
      ]
    },
    {
      "page": "betar_family",
      "title": "Family Objects for (Extended-Support) Beta Regression",
      "topics": [
        "betar_family",
        "xbetax_family"
      ]
    },
    {
      "page": "betareg",
      "title": "Beta Regression for Rates and Proportions",
      "topics": [
        "betareg",
        "betareg.fit"
      ]
    },
    {
      "page": "betareg.control",
      "title": "Control Parameters for Beta Regression",
      "topics": [
        "betareg.control"
      ]
    },
    {
      "page": "betatree",
      "title": "Beta Regression Trees",
      "topics": [
        "betatree",
        "plot.betatree",
        "predict.betatree",
        "print.betatree",
        "sctest.betatree"
      ]
    },
    {
      "page": "CarTask",
      "title": "Partition-Primed Probability Judgement Task for Car Dealership",
      "topics": [
        "CarTask"
      ]
    },
    {
      "page": "FoodExpenditure",
      "title": "Proportion of Household Income Spent on Food",
      "topics": [
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        "Summary",
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