{
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  "Package": "actuaRE",
  "Type": "Package",
  "Title": "Handling Single-Level and Hierarchically Structured Risk Factors\nusing Credibility and Random Effects Models",
  "Version": "1.0.0",
  "Authors@R": "c(person(\"Campo\", \"Bavo D.C.\", role = c(\"aut\", \"cre\"),\nemail = \"bavo.decock@kuleuven.be\"))",
  "Description": "Fits random effects models for\nmulti-level/high-cardinality factors using credibility theory\n(Buhlmann-Straub for single-level, Jewell for hierarchical\nstructures), GLM extensions following Ohlsson (2008)\n<doi:10.1080/03461230701878612>, or Tweedie generalized linear\nmixed models. Provides functions for model fitting,\nvisualization, and prediction. See Campo, B.D.C. and Antonio,\nK. (2023) <doi:10.1080/03461238.2022.2161413>.",
  "License": "GPL (>= 3)",
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  "URL": "https://bavodc.github.io/websiteactuaRE/",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-28 06:54:35 UTC",
    "User": "root"
  },
  "Author": "Campo Bavo D.C. [aut, cre]",
  "Maintainer": "Campo Bavo D.C. <bavo.decock@kuleuven.be>",
  "Config/pak/sysreqs": "cmake make libicu-dev",
  "Repository": "https://bavodc.r-universe.dev",
  "Date/Publication": "2026-02-27 19:05:39 UTC",
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      "package": "nlme",
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    "type": "user",
    "name": "Bavo (De Cock) Campo",
    "description": "Actuarial Data Scientist and Biostatistician"
  },
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    "extra/citation.html",
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    "extra/citation.txt",
    "extra/contents.json",
    "extra/readme.html",
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  "_realowner": "bavodc",
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  "_releases": [
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      "date": "2023-01-25"
    },
    {
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      "date": "2023-02-24"
    },
    {
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    {
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      "date": "2026-02-27"
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  ],
  "_exports": [
    "adjustIntercept",
    "BalanceProperty",
    "buhlmannStraub",
    "buhlmannStraubGLM",
    "buhlmannStraubTweedie",
    "findbars",
    "fitted.buhlmannStraub",
    "fitted.buhlmannStraubGLM",
    "fitted.buhlmannStraubTweedie",
    "fitted.hierCredGLM",
    "fitted.hierCredibility",
    "fitted.hierCredTweedie",
    "fixef",
    "fixef.buhlmannStraubGLM",
    "fixef.buhlmannStraubTweedie",
    "fixef.hierCredGLM",
    "fixef.hierCredTweedie",
    "glFormula",
    "hierCredGLM",
    "hierCredibility",
    "hierCredTweedie",
    "is.formula",
    "isNested",
    "nobars",
    "NrUnique",
    "plotRE",
    "predict.buhlmannStraub",
    "predict.buhlmannStraubGLM",
    "predict.buhlmannStraubTweedie",
    "predict.hierCredGLM",
    "predict.hierCredibility",
    "predict.hierCredTweedie",
    "print.BalanceProperty",
    "print.buhlmannStraub",
    "print.buhlmannStraubGLM",
    "print.buhlmannStraubTweedie",
    "print.hierCredGLM",
    "print.hierCredibility",
    "print.hierCredTweedie",
    "ranef",
    "ranef.buhlmannStraub",
    "ranef.buhlmannStraubGLM",
    "ranef.buhlmannStraubTweedie",
    "ranef.hierCredGLM",
    "ranef.hierCredibility",
    "ranef.hierCredTweedie",
    "summary.buhlmannStraub",
    "summary.buhlmannStraubGLM",
    "summary.buhlmannStraubTweedie",
    "summary.hierCredGLM",
    "summary.hierCredibility",
    "summary.hierCredTweedie",
    "tweedieGLMM",
    "weights.buhlmannStraubGLM",
    "weights.buhlmannStraubTweedie",
    "weights.cpglm",
    "weights.hierCredGLM",
    "weights.hierCredTweedie"
  ],
  "_datasets": [
    {
      "name": "dataCar",
      "title": "data Car",
      "object": "dataCar",
      "class": [
        "data.table",
        "data.frame"
      ],
      "fields": [
        "veh_value",
        "exposure",
        "clm",
        "numclaims",
        "claimcst0",
        "veh_body",
        "veh_age",
        "gender",
        "area",
        "agecat",
        "X_OBSTAT_",
        "Y",
        "w",
        "VehicleType",
        "VehicleBody"
      ],
      "rows": 67566,
      "table": true,
      "tojson": true
    },
    {
      "name": "hachemeisterLong",
      "title": "Hachemeister Data Set",
      "object": "hachemeisterLong",
      "class": [
        "data.frame"
      ],
      "fields": [
        "cohort",
        "state",
        "time",
        "ratio",
        "weight"
      ],
      "rows": 60,
      "table": true,
      "tojson": true
    },
    {
      "name": "tweedietestdata",
      "title": "Simulated data sets to illustrate the package functionality",
      "object": "tweedietestdata",
      "class": [
        "data.table",
        "data.frame"
      ],
      "fields": [
        "y",
        "x1",
        "x2",
        "x3",
        "x4",
        "x5",
        "wt",
        "cluster",
        "subcluster"
      ],
      "rows": 1250,
      "table": true,
      "tojson": true
    },
    {
      "name": "tweedietraindata",
      "title": "Simulated data sets to illustrate the package functionality",
      "object": "tweedietraindata",
      "class": [
        "data.table",
        "data.frame"
      ],
      "fields": [
        "y",
        "x1",
        "x2",
        "x3",
        "x4",
        "x5",
        "wt",
        "cluster",
        "subcluster"
      ],
      "rows": 1250,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "actuaRE",
      "title": "Handling Single-Level and Hierarchically Structured Risk Factors using Credibility and Random Effects Models",
      "topics": [
        "actuaRE-package",
        "actuaRE"
      ]
    },
    {
      "page": "dot-addREs",
      "title": "Add random effects to the data frame",
      "topics": [
        ".addREs"
      ]
    },
    {
      "page": "adjustIntercept",
      "title": "Adjust the intercept to regain the balance property",
      "topics": [
        "adjustIntercept"
      ]
    },
    {
      "page": "BalanceProperty",
      "title": "Balance property",
      "topics": [
        "BalanceProperty"
      ]
    },
    {
      "page": "buhlmannStraub",
      "title": "Buhlmann-Straub credibility model",
      "topics": [
        "buhlmannStraub"
      ]
    },
    {
      "page": "buhlmannStraubGLM",
      "title": "Combining the Buhlmann-Straub credibility model with a GLM (Ohlsson, 2008)",
      "topics": [
        "buhlmannStraubGLM"
      ]
    },
    {
      "page": "buhlmannStraubTweedie",
      "title": "Combining the Buhlmann-Straub credibility model with a Tweedie GLM (Ohlsson, 2008)",
      "topics": [
        "buhlmannStraubTweedie"
      ]
    },
    {
      "page": "dataCar",
      "title": "data Car",
      "topics": [
        "dataCar"
      ]
    },
    {
      "page": "findbars",
      "title": "Determine random-effects expressions from a formula",
      "topics": [
        "findbars"
      ]
    },
    {
      "page": "fixef",
      "title": "Extract fixed-effects estimates",
      "topics": [
        "fixed.effects",
        "fixef"
      ]
    },
    {
      "page": "fixef-actuaRE",
      "title": "Extract the fixed-effects estimates from a fitted random effects model",
      "topics": [
        "fixef-actuaRE",
        "fixef.buhlmannStraubGLM",
        "fixef.buhlmannStraubTweedie",
        "fixef.hierCredGLM",
        "fixef.hierCredTweedie"
      ]
    },
    {
      "page": "hachemeisterLong",
      "title": "Hachemeister Data Set",
      "topics": [
        "hachemeisterLong"
      ]
    },
    {
      "page": "hierCredGLM",
      "title": "Combining the hierarchical credibility model with a GLM (Ohlsson, 2008)",
      "topics": [
        "hierCredGLM"
      ]
    },
    {
      "page": "hierCredGLM-class",
      "title": "Class \"hierCredGLM\" of fitted random effects models estimated with Ohlsson's GLMC algorithm",
      "topics": [
        "fitted.hierCredGLM",
        "hierCredGLM-class",
        "print.hierCredGLM",
        "summary.hierCredGLM"
      ]
    },
    {
      "page": "hierCredibility",
      "title": "Hierarchical credibility model of Jewell",
      "topics": [
        "hierCredibility"
      ]
    },
    {
      "page": "hierCredibility-class",
      "title": "Class \"hierCredibility\" of fitted hierarchical credibility models",
      "topics": [
        "fitted.hierCredibility",
        "hierCredibility-class",
        "print.hierCredibility",
        "summary.hierCredibility"
      ]
    },
    {
      "page": "hierCredTweedie",
      "title": "Combining the hierarchical credibility model with a GLM (Ohlsson, 2008)",
      "topics": [
        "hierCredTweedie"
      ]
    },
    {
      "page": "hierCredTweedie-class",
      "title": "Class \"hierCredTweedie\" of fitted random effects models estimated with Ohlsson's GLMC algorithm",
      "topics": [
        "fitted.hierCredTweedie",
        "hierCredTweedie-class",
        "print.hierCredTweedie",
        "summary.hierCredTweedie"
      ]
    },
    {
      "page": "is.formula",
      "title": "Formula",
      "topics": [
        "is.formula"
      ]
    },
    {
      "page": "isNested",
      "title": "Is f1 nested within f2?",
      "topics": [
        "isNested"
      ]
    },
    {
      "page": "modular",
      "title": "Modular Functions for Mixed Model Fits",
      "topics": [
        "glFormula"
      ]
    },
    {
      "page": "nobars",
      "title": "Omit terms separated by vertical bars in a formula",
      "topics": [
        "nobars"
      ]
    },
    {
      "page": "NrUnique",
      "title": "Number of unique elements in a vector",
      "topics": [
        "NrUnique"
      ]
    },
    {
      "page": "plotRE",
      "title": "Visualizing the random effect estimates using ggplot2",
      "topics": [
        "plotRE"
      ]
    },
    {
      "page": "buhlmannStraub-class",
      "title": "Class \"buhlmannStraub\" of fitted Buhlmann-Straub credibility models",
      "topics": [
        "buhlmannStraub-class",
        "fitted.buhlmannStraub",
        "predict.buhlmannStraub",
        "print.buhlmannStraub",
        "summary.buhlmannStraub"
      ]
    },
    {
      "page": "buhlmannStraubGLM-class",
      "title": "Class \"buhlmannStraubGLM\" of fitted Buhlmann-Straub GLM credibility models",
      "topics": [
        "buhlmannStraubGLM-class",
        "fitted.buhlmannStraubGLM",
        "predict.buhlmannStraubGLM",
        "print.buhlmannStraubGLM",
        "summary.buhlmannStraubGLM"
      ]
    },
    {
      "page": "buhlmannStraubTweedie-class",
      "title": "Class \"buhlmannStraubTweedie\" of fitted Buhlmann-Straub GLM credibility models",
      "topics": [
        "buhlmannStraubTweedie-class",
        "fitted.buhlmannStraubTweedie",
        "predict.buhlmannStraubTweedie",
        "print.buhlmannStraubTweedie",
        "summary.buhlmannStraubTweedie"
      ]
    },
    {
      "page": "predict.hierCredGLM",
      "title": "Model predictions",
      "topics": [
        "predict.hierCredGLM"
      ]
    },
    {
      "page": "predict.hierCredibility",
      "title": "Model predictions",
      "topics": [
        "predict.hierCredibility"
      ]
    },
    {
      "page": "predict.hierCredTweedie",
      "title": "Model predictions",
      "topics": [
        "predict.hierCredTweedie"
      ]
    },
    {
      "page": "print.BalanceProperty",
      "title": "Print method for an object of class 'BalanceProperty'",
      "topics": [
        "print.BalanceProperty"
      ]
    },
    {
      "page": "ranef",
      "title": "Extract the modes of the random effects",
      "topics": [
        "ranef"
      ]
    },
    {
      "page": "ranef-actuaRE",
      "title": "Extract the random effect estimates from a fitted random effects model",
      "topics": [
        "ranef-actuaRE",
        "ranef.buhlmannStraub",
        "ranef.buhlmannStraubGLM",
        "ranef.buhlmannStraubTweedie",
        "ranef.hierCredGLM",
        "ranef.hierCredibility",
        "ranef.hierCredTweedie"
      ]
    },
    {
      "page": "tweedietraindata",
      "title": "Simulated data sets to illustrate the package functionality",
      "topics": [
        "tweedietestdata",
        "tweedietraindata"
      ]
    },
    {
      "page": "tweedieGLMM",
      "title": "Fitting a Tweedie GLMM, using initial estimates from credibility models",
      "topics": [
        "tweedieGLMM"
      ]
    },
    {
      "page": "weights-actuaRE",
      "title": "Extract the model weights",
      "topics": [
        "weights-actuaRE",
        "weights.buhlmannStraubGLM",
        "weights.buhlmannStraubTweedie",
        "weights.cpglm",
        "weights.hierCredGLM",
        "weights.hierCredTweedie"
      ]
    }
  ],
  "_readme": "https://github.com/cran/actuaRE/raw/HEAD/README.md",
  "_rundeps": [
    "biglm",
    "boot",
    "cli",
    "coda",
    "cplm",
    "cpp11",
    "data.table",
    "DBI",
    "farver",
    "ggplot2",
    "glue",
    "gtable",
    "isoband",
    "labeling",
    "lattice",
    "lifecycle",
    "lme4",
    "magrittr",
    "MASS",
    "Matrix",
    "minqa",
    "nlme",
    "nloptr",
    "plyr",
    "R6",
    "rbibutils",
    "RColorBrewer",
    "Rcpp",
    "RcppEigen",
    "Rdpack",
    "reformulas",
    "reshape2",
    "rlang",
    "S7",
    "scales",
    "statmod",
    "stringi",
    "stringr",
    "tweedie",
    "vctrs",
    "viridisLite",
    "withr"
  ],
  "_vignettes": [
    {
      "source": "actuaRE.Rmd",
      "filename": "actuaRE.html",
      "title": "Introduction to actuaRE",
      "author": "Bavo D.C. Campo",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Summary of available functions",
        "Handling multi-level factors using random effects models",
        "Random effects model structures",
        "Single-level random effects",
        "Hierarchical (two-level) random effects",
        "Just the code please",
        "Example data sets",
        "Buhlmann-Straub credibility model (single random effect)",
        "Hierarchical credibility model (two-level random effects)",
        "Combining credibility models with a GLM",
        "Single random effect with GLM",
        "Hierarchical random effects with GLM",
        "Mixed models",
        "Single random effect GLMM",
        "Nested random effects GLMM",
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