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  "Title": "Accurate Generalized Linear Model",
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  "Description": "Provides functions to fit Accurate Generalized Linear\nModel (AGLM) models, visualize them, and predict for new data.\nAGLM is defined as a regularized GLM which applies a sort of\nfeature transformations using a discretization of numerical\nfeatures and specific coding methodologies of dummy variables.\nFor more information on AGLM, see Suguru Fujita, Toyoto Tanaka,\nKenji Kondo and Hirokazu Iwasawa (2020)\n<https://www.institutdesactuaires.com/global/gene/link.php?doc_id=16273&fg=1>.",
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  "License": "GPL-2",
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  "Repository": "https://kkondo1981.r-universe.dev",
  "Date/Publication": "2025-05-11 15:58:19 UTC",
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    "createEqualFreqBins",
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    "cva.aglm",
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    "getLVarMatForOneVec",
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    {
      "page": "aglm-package",
      "title": "aglm: Accurate Generalized Linear Model",
      "topics": [
        "aglm-package"
      ]
    },
    {
      "page": "AccurateGLM-class",
      "title": "Class for results of 'aglm()' and 'cv.aglm()'",
      "topics": [
        "AccurateGLM-class"
      ]
    },
    {
      "page": "aglm",
      "title": "Fit an AGLM model with no cross-validation",
      "topics": [
        "aglm"
      ]
    },
    {
      "page": "AGLM_Input-class",
      "title": "S4 class for input",
      "topics": [
        "AGLM_Input-class"
      ]
    },
    {
      "page": "coef.AccurateGLM",
      "title": "Get coefficients",
      "topics": [
        "coef.AccurateGLM"
      ]
    },
    {
      "page": "createEqualFreqBins",
      "title": "Create bins (equal frequency binning)",
      "topics": [
        "createEqualFreqBins"
      ]
    },
    {
      "page": "createEqualWidthBins",
      "title": "Create bins (equal width binning)",
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        "createEqualWidthBins"
      ]
    },
    {
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      "title": "Fit an AGLM model with cross-validation for lambda",
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      ]
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      "page": "CVA_AccurateGLM-class",
      "title": "Class for results of 'cva.aglm()'",
      "topics": [
        "CVA_AccurateGLM-class"
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    },
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      "title": "Fit an AGLM model with cross-validation for both alpha and lambda",
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        "cva.aglm"
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    },
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      "title": "Get deviance",
      "topics": [
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      ]
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    },
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      "topics": [
        "getODummyMatForOneVec"
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    },
    {
      "page": "getUDummyMatForOneVec",
      "title": "Create a U-dummy matrix for one variable",
      "topics": [
        "getUDummyMatForOneVec"
      ]
    },
    {
      "page": "plot.AccurateGLM",
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      "topics": [
        "plot.AccurateGLM"
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    },
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      ]
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