{
  "_id": "6a196d32acfb0bcc41deb107",
  "Package": "enrichwith",
  "Title": "Methods to Enrich R Objects with Extra Components",
  "Version": "0.5.0",
  "Authors@R": "person(\"Ioannis\", \"Kosmidis\", email = \"ioannis.kosmidis@warwick.ac.uk\", role = c(\"aut\", \"cre\"))",
  "Description": "Provides the \"enrich()\" method for augmenting list-like R\nobjects with additional, model-specific components. Methods are\ncurrently available for objects of class \"family\", \"link-glm\",\n\"lm\", \"glm\", and \"betareg\". Enriched objects retain their\noriginal class and remain compatible with existing methods. For\nexample, enriching a \"glm\" object produces an \"enriched_glm\"\nobject that also inherits from \"glm\". In addition to the\nstandard components, the \"enriched_glm\" object includes methods\nfor simulation and functions to compute scores, observed and\nexpected information matrices, first-order bias, and other\nmodel quantities such as densities, probabilities, and\nquantiles, which can be evaluated at use-supplied parameter\nvalues. The package also provides tools for generating\ncustomizable source code templates for the structured\nimplementation of methods to compute new components and enrich\narbitrary objects.",
  "URL": "https://github.com/ikosmidis/enrichwith",
  "BugReports": "https://github.com/ikosmidis/enrichwith/issues",
  "License": "GPL-3",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RoxygenNote": "7.3.3",
  "VignetteBuilder": "knitr",
  "Repository": "https://ikosmidis.r-universe.dev",
  "Date/Publication": "2026-04-29 15:53:15 UTC",
  "RemoteUrl": "https://github.com/ikosmidis/enrichwith",
  "RemoteRef": "HEAD",
  "RemoteSha": "fdd0dbb467ada6b9cffdb0335e541eaf2b659bf0",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-29 08:50:44 UTC",
    "User": "root"
  },
  "Author": "Ioannis Kosmidis [aut, cre]",
  "Maintainer": "Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>",
  "MD5sum": "27e8ee4970002e40e85a949255ebe54e",
  "_user": "ikosmidis",
  "_type": "src",
  "_file": "enrichwith_0.5.0.tar.gz",
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  "_created": "2026-05-29T08:50:44.000Z",
  "_published": "2026-05-29T10:40:50.107Z",
  "_distro": "noble",
  "_jobs": [
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  "_buildurl": "https://github.com/r-universe/ikosmidis/actions/runs/26627673545",
  "_status": "success",
  "_host": "GitHub-Actions",
  "_upstream": "https://github.com/ikosmidis/enrichwith",
  "_commit": {
    "id": "fdd0dbb467ada6b9cffdb0335e541eaf2b659bf0",
    "author": "Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>",
    "committer": "Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>",
    "message": "On CRAN\n",
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  "_maintainer": {
    "name": "Ioannis Kosmidis",
    "email": "ioannis.kosmidis@warwick.ac.uk",
    "login": "ikosmidis",
    "mastodon": "@ikosmidis@fosstodon.org",
    "twitter": "@IKosmidis_",
    "description": "Professor of Statistics at #warwickuni;\ninterested in methods for statistical learning and inference, computing and programming (mainly R & Julia)",
    "uuid": 15086307
  },
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  "_dependencies": [
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      "package": "R",
      "version": ">= 3.0.0",
      "role": "Depends"
    },
    {
      "package": "whisker",
      "role": "Suggests"
    },
    {
      "package": "SuppDists",
      "role": "Suggests"
    },
    {
      "package": "brglm",
      "role": "Suggests"
    },
    {
      "package": "brglm2",
      "role": "Suggests"
    },
    {
      "package": "ggplot2",
      "role": "Suggests"
    },
    {
      "package": "MASS",
      "role": "Suggests"
    },
    {
      "package": "knitr",
      "role": "Suggests"
    },
    {
      "package": "rmarkdown",
      "role": "Suggests"
    },
    {
      "package": "testthat",
      "role": "Suggests"
    },
    {
      "package": "numDeriv",
      "role": "Suggests"
    },
    {
      "package": "betareg",
      "role": "Enhances"
    },
    {
      "package": "gnm",
      "role": "Enhances"
    },
    {
      "package": "stats",
      "role": "Enhances"
    }
  ],
  "_owner": "ikosmidis",
  "_selfowned": true,
  "_usedby": 19,
  "_updates": [
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    },
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    },
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  ],
  "_tags": [
    {
      "name": "v0.5",
      "date": "2026-04-29"
    }
  ],
  "_topics": [
    "infrastructure"
  ],
  "_stars": 5,
  "_contributors": [
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      "user": "ikosmidis",
      "count": 195,
      "uuid": 15086307
    }
  ],
  "_userbio": {
    "uuid": 15086307,
    "type": "user",
    "name": "Ioannis Kosmidis",
    "description": "Professor of Statistics at #warwickuni;\r\ninterested in methods for statistical learning and inference, computing and programming (mainly R & Julia)"
  },
  "_downloads": {
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/enrichwith"
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  "_devurl": "https://github.com/ikosmidis/enrichwith",
  "_searchresults": 16,
  "_rbuild": "4.6.0",
  "_assets": [
    "extra/citation.cff",
    "extra/citation.html",
    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/enrichwith.html",
    "extra/NEWS.html",
    "extra/NEWS.txt",
    "extra/readme.html",
    "extra/readme.md",
    "manual.pdf"
  ],
  "_homeurl": "https://github.com/ikosmidis/enrichwith",
  "_realowner": "ikosmidis",
  "_cranurl": true,
  "_releases": [
    {
      "version": "0.0.1",
      "date": "2016-08-08"
    },
    {
      "version": "0.0.2",
      "date": "2016-09-03"
    },
    {
      "version": "0.0.3",
      "date": "2017-03-07"
    },
    {
      "version": "0.0.4",
      "date": "2017-05-12"
    },
    {
      "version": "0.0.5",
      "date": "2017-10-07"
    },
    {
      "version": "0.1",
      "date": "2017-11-06"
    },
    {
      "version": "0.1.1",
      "date": "2018-05-04"
    },
    {
      "version": "0.2",
      "date": "2019-01-11"
    },
    {
      "version": "0.3",
      "date": "2019-10-14"
    },
    {
      "version": "0.3.1",
      "date": "2020-01-10"
    },
    {
      "version": "0.4.0",
      "date": "2025-09-08"
    },
    {
      "version": "0.5.0",
      "date": "2026-04-29"
    }
  ],
  "_exports": [
    "create_enrichwith_skeleton",
    "enrich",
    "enriched_glm",
    "get_auxiliary_functions",
    "get_bias_function",
    "get_dmodel_function",
    "get_enrichment_options",
    "get_information_function",
    "get_pmodel_function",
    "get_qmodel_function",
    "get_score_function",
    "get_simulate_function"
  ],
  "_datasets": [
    {
      "name": "endometrial",
      "title": "Histology grade and risk factors for 79 cases of endometrial cancer",
      "object": "endometrial",
      "class": [
        "data.frame"
      ],
      "fields": [
        "NV",
        "PI",
        "EH",
        "HG"
      ],
      "rows": 79,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "coef.enriched_glm",
      "title": "Function to extract model coefficients from objects of class 'enriched_glm'",
      "topics": [
        "coef.enriched_glm"
      ]
    },
    {
      "page": "coef.enriched_lm",
      "title": "Function to extract model coefficients from objects of class 'enriched_lm'",
      "topics": [
        "coef.enriched_lm"
      ]
    },
    {
      "page": "create_enrichwith_skeleton",
      "title": "Create a enrichwith skeleton",
      "topics": [
        "create_enrichwith_skeleton"
      ]
    },
    {
      "page": "endometrial",
      "title": "Histology grade and risk factors for 79 cases of endometrial cancer",
      "topics": [
        "endometrial"
      ]
    },
    {
      "page": "enrich",
      "title": "Generic method for enriching objects",
      "topics": [
        "enrich"
      ]
    },
    {
      "page": "enrich.betareg",
      "title": "Enrich objects of class betareg",
      "topics": [
        "enrich.betareg"
      ]
    },
    {
      "page": "enrich.family",
      "title": "Enrich objects of class 'family'",
      "topics": [
        "enrich.family"
      ]
    },
    {
      "page": "enrich.glm",
      "title": "Enrich objects of class 'glm'",
      "topics": [
        "enrich.glm"
      ]
    },
    {
      "page": "enrich.link-glm",
      "title": "Enrich objects of class 'link-glm'",
      "topics": [
        "enrich.link-glm"
      ]
    },
    {
      "page": "enrich.lm",
      "title": "Enrich objects of class 'lm'",
      "topics": [
        "enrich.lm"
      ]
    },
    {
      "page": "enriched_glm",
      "title": "Fitting generalized linear models enriched with useful components",
      "topics": [
        "enriched_glm"
      ]
    },
    {
      "page": "enrichwith",
      "title": "Methods to enrich list-like R objects with extra components",
      "topics": [
        "enrichwith-package",
        "enrichwith"
      ]
    },
    {
      "page": "get_auxiliary_functions",
      "title": "Generic method for extracting or computing auxiliary functions for objects",
      "topics": [
        "get_auxiliary_functions"
      ]
    },
    {
      "page": "get_auxiliary_functions.betareg",
      "title": "Function to compute/extract auxiliary functions from objects of class 'betreg'/'enriched_betareg'",
      "topics": [
        "get_auxiliary_functions.betareg"
      ]
    },
    {
      "page": "get_auxiliary_functions.glm",
      "title": "Function to compute/extract auxiliary functions from objects of class 'glm'/'enriched_glm'",
      "topics": [
        "get_auxiliary_functions.glm"
      ]
    },
    {
      "page": "get_auxiliary_functions.lm",
      "title": "Function to compute/extract auxiliary functions from objects of class 'lm'/'enriched_lm'",
      "topics": [
        "get_auxiliary_functions.lm"
      ]
    },
    {
      "page": "get_bias_function",
      "title": "Generic method for extracting or computing a function that returns the bias for the parameters in modelling objects",
      "topics": [
        "get_bias_function"
      ]
    },
    {
      "page": "get_bias_function.betareg",
      "title": "Function to compute/extract a function that returns the first term in the expansion of the bias of the MLE for the parameters of an object of class 'betareg'/'enriched_betareg'",
      "topics": [
        "get_bias_function.betareg"
      ]
    },
    {
      "page": "get_bias_function.glm",
      "title": "Function to compute/extract a function that returns the first term in the expansion of the bias of the MLE for the parameters of an object of class 'glm'/'enriched_glm'",
      "topics": [
        "get_bias_function.glm"
      ]
    },
    {
      "page": "get_bias_function.lm",
      "title": "Function to compute/extract a function that returns the first term in the expansion of the bias of the MLE for the parameters of an object of class 'lm'/'enriched_lm'",
      "topics": [
        "get_bias_function.lm"
      ]
    },
    {
      "page": "get_dmodel_function",
      "title": "Generic method for extracting or computing a dmodel function for modelling objects",
      "topics": [
        "get_dmodel_function"
      ]
    },
    {
      "page": "get_dmodel_function.glm",
      "title": "Function to compute/extract a 'dmodel' function",
      "topics": [
        "get_dmodel_function.glm"
      ]
    },
    {
      "page": "get_enrichment_options",
      "title": "Generic method for getting available options for the enrichment of objects",
      "topics": [
        "get_enrichment_options",
        "print.enrichment_options"
      ]
    },
    {
      "page": "get_enrichment_options.betareg",
      "title": "Available options for the enrichment objects of class betareg",
      "topics": [
        "get_enrichment_options.betareg"
      ]
    },
    {
      "page": "get_enrichment_options.family",
      "title": "Available options for the enrichment objects of class family",
      "topics": [
        "get_enrichment_options.family"
      ]
    },
    {
      "page": "get_enrichment_options.glm",
      "title": "Available options for the enrichment objects of class 'glm'",
      "topics": [
        "get_enrichment_options.glm"
      ]
    },
    {
      "page": "get_enrichment_options.link-glm",
      "title": "Available options for the enrichment objects of class link-glm",
      "topics": [
        "get_enrichment_options.link-glm"
      ]
    },
    {
      "page": "get_enrichment_options.lm",
      "title": "Available options for the enrichment objects of class 'lm'",
      "topics": [
        "get_enrichment_options.lm"
      ]
    },
    {
      "page": "get_information_function",
      "title": "Generic method for extracting or computing a function that returns the information matrix for modelling objects",
      "topics": [
        "get_information_function"
      ]
    },
    {
      "page": "get_information_function.betareg",
      "title": "Function to compute/extract a function that returns the information matrix for an object of class 'betareg'/'enriched_betareg'",
      "topics": [
        "get_information_function.betareg"
      ]
    },
    {
      "page": "get_information_function.glm",
      "title": "Function to compute/extract a function that returns the information matrix for an object of class 'glm'/'enriched_glm'",
      "topics": [
        "get_information_function.glm"
      ]
    },
    {
      "page": "get_information_function.lm",
      "title": "Function to compute/extract a function that returns the information matrix for an object of class 'lm'/'enriched_lm'",
      "topics": [
        "get_information_function.lm"
      ]
    },
    {
      "page": "get_pmodel_function",
      "title": "Generic method for extracting or computing a pmodel function for modelling objects",
      "topics": [
        "get_pmodel_function"
      ]
    },
    {
      "page": "get_pmodel_function.glm",
      "title": "Function to compute/extract a 'pmodel' function",
      "topics": [
        "get_pmodel_function.glm"
      ]
    },
    {
      "page": "get_qmodel_function",
      "title": "Generic method for extracting or computing a qmodel function for modelling objects",
      "topics": [
        "get_qmodel_function"
      ]
    },
    {
      "page": "get_qmodel_function.glm",
      "title": "Function to compute/extract a 'qmodel' function",
      "topics": [
        "get_qmodel_function.glm"
      ]
    },
    {
      "page": "get_score_function",
      "title": "Generic method for extracting or computing a function that returns the scores for modelling objects",
      "topics": [
        "get_score_function"
      ]
    },
    {
      "page": "get_score_function.betareg",
      "title": "Function to compute/extract a function that returns the scores (derivatives of the log-likelihood) for an object of class 'betareg'/'enriched_betareg'",
      "topics": [
        "get_score_function.betareg"
      ]
    },
    {
      "page": "get_score_function.glm",
      "title": "Function to compute/extract a function that returns the scores (derivatives of the log-likelihood) for an object of class 'glm'/'enriched_glm'",
      "topics": [
        "get_score_function.glm"
      ]
    },
    {
      "page": "get_score_function.lm",
      "title": "Function to compute/extract a function that returns the scores (derivatives of the log-likelihood) for an object of class 'lm'/'enriched_lm'",
      "topics": [
        "get_score_function.lm"
      ]
    },
    {
      "page": "get_simulate_function",
      "title": "Generic method for extracting or computing a simulate function for modelling objects",
      "topics": [
        "get_simulate_function"
      ]
    },
    {
      "page": "get_simulate_function.betareg",
      "title": "Function to compute/extract a simulate function for response vectors from an object of class 'betareg'/'enriched_betareg'",
      "topics": [
        "get_simulate_function.betareg"
      ]
    },
    {
      "page": "get_simulate_function.glm",
      "title": "Function to compute/extract a simulate function for response vectors from an object of class 'glm'/'enriched_glm'",
      "topics": [
        "get_simulate_function.glm"
      ]
    },
    {
      "page": "get_simulate_function.lm",
      "title": "Function to compute/extract a simulate function for response vectors from an object of class 'lm'/'enriched_lm'",
      "topics": [
        "get_simulate_function.lm"
      ]
    }
  ],
  "_readme": "https://github.com/ikosmidis/enrichwith/raw/HEAD/README.md",
  "_rundeps": [],
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      "source": "bias.Rmd",
      "filename": "bias.html",
      "title": "Bias reduction in generalized linear models using enrichwith",
      "author": "Ioannis Kosmidis",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Endometrial cancer data",
        "Quasi Fisher scoring for bias reduction",
        "Implementation using enrichwith",
        "Notes",
        "References"
      ],
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      "filename": "exponential_family.html",
      "title": "Enriching family objects: exponential family of distributions",
      "author": "Ioannis Kosmidis",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Exponential family and family objects",
        "Normal with mean $\\mu$ and variance $\\phi/m$",
        "Binomial with index $m$ and probability $\\mu$",
        "Poisson with mean $\\mu$",
        "Gamma with mean $\\mu$ and shape $1/\\phi$",
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        "Components in family objects",
        "Enrichment options for family objects"
      ],
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    },
    {
      "source": "GLMs.Rmd",
      "filename": "GLMs.html",
      "title": "Enriching glm objects",
      "author": "Ioannis Kosmidis",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "Clotting data set",
        "Key quantities in likelihood inference",
        "Score function",
        "Information matrix",
        "Score tests",
        "Simulating from glm objects at parameter values",
        "pmodel, dmodel, qmodel",
        "enriched_glm",
        "Links to other resources",
        "References"
      ],
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      "modified": "2025-09-08 13:16:39",
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