{
  "_id": "6a1fe401b401979e7343bbb4",
  "Package": "crch",
  "Title": "Censored Regression with Conditional Heteroscedasticity",
  "Version": "1.2-2",
  "Date": "2025-07-28",
  "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 = c(\"Jakob\", \"W.\"), family = \"Messner\", role = \"aut\", email = \"jakob.messner@posteo.net\", comment = c(ORCID = \"0000-0002-1027-3673\")),\nperson(given = \"Reto\", family = \"Stauffer\", role = \"aut\", email = \"reto.stauffer@uibk.ac.at\", comment = c(ORCID = \"0000-0002-3798-5507\")),\nperson(given = \"Ioannis\", family = \"Kosmidis\", role = \"ctb\", email = \"ioannis.kosmidis@warwick.ac.uk\", comment = c(ORCID = \"0000-0003-1556-0302\")),\nperson(given = c(\"Georg\", \"J.\"), family = \"Mayr\", role = \"ctb\", email = \"Georg.Mayr@uibk.ac.at\", comment = c(ORCID = \"0000-0001-6661-9453\")))",
  "Description": "Different approaches to censored or truncated regression\nwith conditional heteroscedasticity are provided. First,\ncontinuous distributions can be used for the (right and/or left\ncensored or truncated) response with separate linear predictors\nfor the mean and variance. Second, cumulative link models for\nordinal data (obtained by interval-censoring continuous data)\ncan be employed for heteroscedastic extended logistic\nregression (HXLR). In the latter type of models, the intercepts\ndepend on the thresholds that define the intervals.\nInfrastructure for working with censored or truncated normal,\nlogistic, and Student-t distributions, i.e., d/p/q/r functions\nand distributions3 objects.",
  "License": "GPL-2 | GPL-3",
  "URL": "https://topmodels.R-Forge.R-project.org/crch/",
  "BugReports": "https://topmodels.R-Forge.R-project.org/crch/contact.html",
  "Encoding": "UTF-8",
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  "Repository": "https://zeileis.r-universe.dev",
  "Date/Publication": "2025-09-26 18:37:17 UTC",
  "RemoteUrl": "https://github.com/r-forge/topmodels",
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  "RemoteSubdir": "pkg/crch",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-06-03 08:16:04 UTC",
    "User": "root"
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  "Author": "Achim Zeileis [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-0918-3766>),\nJakob W. Messner [aut] (ORCID: <https://orcid.org/0000-0002-1027-3673>),\nReto Stauffer [aut] (ORCID: <https://orcid.org/0000-0002-3798-5507>),\nIoannis Kosmidis [ctb] (ORCID: <https://orcid.org/0000-0003-1556-0302>),\nGeorg J. Mayr [ctb] (ORCID: <https://orcid.org/0000-0001-6661-9453>)",
  "Maintainer": "Achim Zeileis <Achim.Zeileis@R-project.org>",
  "MD5sum": "fc4f5bd258787672f3d5ad13fae9da84",
  "_user": "zeileis",
  "_type": "src",
  "_file": "crch_1.2-2.tar.gz",
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  "_created": "2026-06-03T08:16:04.000Z",
  "_published": "2026-06-03T08:21:21.809Z",
  "_distro": "noble",
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    "message": "feat: Started adding parallelization to pdf.distribution\n\ngit-svn-id: svn://svn.r-forge.r-project.org/svnroot/topmodels@1909 edb9625f-4e0d-4859-8d74-9fd3b1da38cb\n",
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      "date": "2015-06-27"
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      "date": "2015-08-06"
    },
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  "_exports": [
    "CensoredLogistic",
    "CensoredNormal",
    "CensoredStudentsT",
    "crch",
    "crch.boost",
    "crch.boost.fit",
    "crch.control",
    "crch.fit",
    "crch.stabsel",
    "dclogis",
    "dcnorm",
    "dct",
    "dtlogis",
    "dtnorm",
    "dtt",
    "getSummary.crch",
    "hxlr",
    "hxlr.control",
    "pclogis",
    "pcnorm",
    "pct",
    "ptlogis",
    "ptnorm",
    "ptt",
    "qclogis",
    "qcnorm",
    "qct",
    "qtlogis",
    "qtnorm",
    "qtt",
    "rclogis",
    "rcnorm",
    "rct",
    "rtlogis",
    "rtnorm",
    "rtt",
    "trch",
    "TruncatedLogistic",
    "TruncatedNormal",
    "TruncatedStudentsT"
  ],
  "_datasets": [
    {
      "name": "RainIbk",
      "title": "Precipitation Observations and Forecasts for Innsbruck",
      "object": "RainIbk",
      "file": "RainIbk.rda",
      "class": [
        "data.frame"
      ],
      "fields": [
        "rain",
        "rainfc.1",
        "rainfc.2",
        "rainfc.3",
        "rainfc.4",
        "rainfc.5",
        "rainfc.6",
        "rainfc.7",
        "rainfc.8",
        "rainfc.9",
        "rainfc.10",
        "rainfc.11"
      ],
      "rows": 4971,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "CensoredLogistic",
      "title": "Create a Censored Logistic Distribution",
      "topics": [
        "cdf.CensoredLogistic",
        "CensoredLogistic",
        "crps.CensoredLogistic",
        "is_continuous.CensoredLogistic",
        "is_discrete.CensoredLogistic",
        "kurtosis.CensoredLogistic",
        "log_pdf.CensoredLogistic",
        "mean.CensoredLogistic",
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        "quantile.CensoredLogistic",
        "random.CensoredLogistic",
        "skewness.CensoredLogistic",
        "support.CensoredLogistic",
        "variance.CensoredLogistic"
      ]
    },
    {
      "page": "CensoredNormal",
      "title": "Create a Censored Normal Distribution",
      "topics": [
        "cdf.CensoredNormal",
        "CensoredNormal",
        "crps.CensoredNormal",
        "is_continuous.CensoredNormal",
        "is_discrete.CensoredNormal",
        "kurtosis.CensoredNormal",
        "log_pdf.CensoredNormal",
        "mean.CensoredNormal",
        "pdf.CensoredNormal",
        "quantile.CensoredNormal",
        "random.CensoredNormal",
        "skewness.CensoredNormal",
        "support.CensoredNormal",
        "variance.CensoredNormal"
      ]
    },
    {
      "page": "CensoredStudentsT",
      "title": "Create a Censored Student's T Distribution",
      "topics": [
        "cdf.CensoredStudentsT",
        "CensoredStudentsT",
        "crps.CensoredStudentsT",
        "is_continuous.CensoredStudentsT",
        "is_discrete.CensoredStudentsT",
        "kurtosis.CensoredStudentsT",
        "log_pdf.CensoredStudentsT",
        "mean.CensoredStudentsT",
        "pdf.CensoredStudentsT",
        "quantile.CensoredStudentsT",
        "random.CensoredStudentsT",
        "skewness.CensoredStudentsT",
        "support.CensoredStudentsT",
        "variance.CensoredStudentsT"
      ]
    },
    {
      "page": "clogis",
      "title": "The Censored Logistic Distribution",
      "topics": [
        "dclogis",
        "pclogis",
        "qclogis",
        "rclogis"
      ]
    },
    {
      "page": "cnorm",
      "title": "The Censored Normal Distribution",
      "topics": [
        "dcnorm",
        "pcnorm",
        "qcnorm",
        "rcnorm"
      ]
    },
    {
      "page": "coef.crch",
      "title": "Methods for Fitted crch Models",
      "topics": [
        "coef.crch",
        "crps.crch",
        "estfun.crch",
        "fitted.crch",
        "getSummary.crch",
        "logLik.crch",
        "model.frame.crch",
        "model.matrix.crch",
        "print.crch",
        "print.summary.crch",
        "residuals.crch",
        "summary.crch",
        "terms.crch",
        "vcov.crch"
      ]
    },
    {
      "page": "coef.crch.boost",
      "title": "Methods for Boosted crch Models",
      "topics": [
        "coef.crch.boost",
        "logLik.crch.boost",
        "print.crch.boost",
        "print.summary.crch.boost",
        "summary.crch.boost"
      ]
    },
    {
      "page": "coef.hxlr",
      "title": "Methods for Fitted hxlr Models",
      "topics": [
        "coef.hxlr",
        "logLik.hxlr",
        "print.hxlr",
        "print.summary.hxlr",
        "summary.hxlr",
        "terms.hxlr",
        "vcov.hxlr"
      ]
    },
    {
      "page": "crch",
      "title": "Censored and Truncated Regression with Conditional Heteroscedasticy",
      "topics": [
        "crch",
        "crch.fit",
        "trch"
      ]
    },
    {
      "page": "crch.boost",
      "title": "Auxiliary Functions for Boosting crch Models",
      "concept": [
        "boosting"
      ],
      "topics": [
        "crch.boost",
        "crch.boost.fit"
      ]
    },
    {
      "page": "crch.control",
      "title": "Control Options for crch Models",
      "topics": [
        "crch.control"
      ]
    },
    {
      "page": "crch.stabsel",
      "title": "Auxiliary Functions for Stability Selection Using Boosting",
      "topics": [
        "crch.stabsel"
      ]
    },
    {
      "page": "ct",
      "title": "The Censored Student-t Distribution",
      "topics": [
        "dct",
        "pct",
        "qct",
        "rct"
      ]
    },
    {
      "page": "hxlr",
      "title": "Heteroscedastic Extended Logistic Regression",
      "topics": [
        "hxlr"
      ]
    },
    {
      "page": "hxlr.control",
      "title": "Control Options for hxlr Models",
      "topics": [
        "hxlr.control"
      ]
    },
    {
      "page": "plot.crch.boost",
      "title": "Visualizing Coefficient Paths for Boosted crch Models",
      "topics": [
        "plot.crch.boost"
      ]
    },
    {
      "page": "predict.crch",
      "title": "Predictions for Fitted crch Models",
      "topics": [
        "predict.crch",
        "prodist.crch"
      ]
    },
    {
      "page": "predict.crch.boost",
      "title": "Predictions for Boosted crch Models",
      "topics": [
        "predict.crch.boost"
      ]
    },
    {
      "page": "predict.hxlr",
      "title": "Predictions for Fitted hxlr Models",
      "topics": [
        "fitted.hxlr",
        "predict.hxlr"
      ]
    },
    {
      "page": "RainIbk",
      "title": "Precipitation Observations and Forecasts for Innsbruck",
      "topics": [
        "RainIbk"
      ]
    },
    {
      "page": "tlogis",
      "title": "The Truncated Logistic Distribution",
      "topics": [
        "dtlogis",
        "ptlogis",
        "qtlogis",
        "rtlogis"
      ]
    },
    {
      "page": "tnorm",
      "title": "The Truncated Normal Distribution",
      "topics": [
        "dtnorm",
        "ptnorm",
        "qtnorm",
        "rtnorm"
      ]
    },
    {
      "page": "TruncatedLogistic",
      "title": "Create a Truncated Logistic Distribution",
      "topics": [
        "cdf.TruncatedLogistic",
        "crps.TruncatedLogistic",
        "is_continuous.TruncatedLogistic",
        "is_discrete.TruncatedLogistic",
        "kurtosis.TruncatedLogistic",
        "log_pdf.TruncatedLogistic",
        "mean.TruncatedLogistic",
        "pdf.TruncatedLogistic",
        "quantile.TruncatedLogistic",
        "random.TruncatedLogistic",
        "skewness.TruncatedLogistic",
        "support.TruncatedLogistic",
        "TruncatedLogistic",
        "variance.TruncatedLogistic"
      ]
    },
    {
      "page": "TruncatedNormal",
      "title": "Create a Truncated Normal Distribution",
      "topics": [
        "cdf.TruncatedNormal",
        "crps.TruncatedNormal",
        "is_continuous.TruncatedNormal",
        "is_discrete.TruncatedNormal",
        "kurtosis.TruncatedNormal",
        "log_pdf.TruncatedNormal",
        "mean.TruncatedNormal",
        "pdf.TruncatedNormal",
        "quantile.TruncatedNormal",
        "random.TruncatedNormal",
        "skewness.TruncatedNormal",
        "support.TruncatedNormal",
        "TruncatedNormal",
        "variance.TruncatedNormal"
      ]
    },
    {
      "page": "TruncatedStudentsT",
      "title": "Create a Truncated Student's T Distribution",
      "topics": [
        "cdf.TruncatedStudentsT",
        "crps.TruncatedStudentsT",
        "is_continuous.TruncatedStudentsT",
        "is_discrete.TruncatedStudentsT",
        "kurtosis.TruncatedStudentsT",
        "log_pdf.TruncatedStudentsT",
        "mean.TruncatedStudentsT",
        "pdf.TruncatedStudentsT",
        "quantile.TruncatedStudentsT",
        "random.TruncatedStudentsT",
        "skewness.TruncatedStudentsT",
        "support.TruncatedStudentsT",
        "TruncatedStudentsT",
        "variance.TruncatedStudentsT"
      ]
    },
    {
      "page": "tt",
      "title": "The Truncated Student-t Distribution",
      "topics": [
        "dtt",
        "ptt",
        "qtt",
        "rtt"
      ]
    }
  ],
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