{
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  "Package": "GAGAs",
  "Type": "Package",
  "Title": "Global Adaptive Generative Adjustment Algorithm for Generalized\nLinear Models",
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  "Language": "en-US",
  "Authors@R": "c(\nperson(\"Bin\", \"Wang\", role=c(\"aut\", \"cre\"), email=\"eatingbeen@hotmail.com\"),\nperson(\"Xiaofei\", \"Wang\", role=c(\"ctb\")),\nperson(\"Jianhua\", \"Guo\", role=c(\"ths\"))\n)",
  "Description": "Fits linear regression, logistic and multinomial\nregression models, Poisson regression, Cox model via Global\nAdaptive Generative Adjustment Algorithm. For more detailed\ninformation, see Bin Wang, Xiaofei Wang and Jianhua Guo (2022)\n<arXiv:1911.00658>. This paper provides the theoretical\nproperties of Gaga linear model when the load matrix is\northogonal. Further study is going on for the nonorthogonal\ncases and generalized linear models. These works are in part\nsupported by the National Natural Foundation of China\n(No.12171076).",
  "License": "GPL-2",
  "URL": "https://arxiv.org/abs/1911.00658",
  "Encoding": "UTF-8",
  "SystemRequirements": "C++17",
  "RoxygenNote": "7.2.3",
  "Maintainer": "Bin Wang <eatingbeen@hotmail.com>",
  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-06-05 09:22:33 UTC",
    "User": "root"
  },
  "Author": "Bin Wang [aut, cre], Xiaofei Wang [ctb], Jianhua Guo [ths]",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2024-01-24 02:40:50 UTC",
  "RemoteUrl": "https://github.com/cran/GAGAs",
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    "extra/citation.json",
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      "date": "2023-03-30"
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    "cal.acc",
    "cal.cindex",
    "cal.F1Score",
    "cal.w.acc",
    "cox_GAGA",
    "GAGAs",
    "LM_GAGA",
    "logistic_GAGA",
    "multinomial_GAGA",
    "poisson_GAGA",
    "predict.GAGA",
    "summary.GAGA"
  ],
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    {
      "page": "cal.acc",
      "title": "Calculate ACC for classification, the inputs must be characters",
      "topics": [
        "cal.acc"
      ]
    },
    {
      "page": "cal.cindex",
      "title": "compute C index for a Cox model",
      "topics": [
        "cal.cindex"
      ]
    },
    {
      "page": "cal.F1Score",
      "title": "Calculate F1 score for classification, the inputs must be characters, and each of these elements must be either 'FALSE' or 'TRUE'.",
      "topics": [
        "cal.F1Score"
      ]
    },
    {
      "page": "cal.w.acc",
      "title": "Calculate the weighted ACC of the classification, the inputs must be characters",
      "topics": [
        "cal.w.acc"
      ]
    },
    {
      "page": "cox_GAGA",
      "title": "Fit a Cox model via the GAGA algorithm.",
      "topics": [
        "cox_GAGA"
      ]
    },
    {
      "page": "cpp_COX_gaga",
      "title": "Fit a Cox model via the GAGA algorithm using cpp.",
      "topics": [
        "cpp_COX_gaga"
      ]
    },
    {
      "page": "cpp_logistic_gaga",
      "title": "Fit a logistic model via the Global Adaptive Generative Adjustment algorithm using cpp",
      "topics": [
        "cpp_logistic_gaga"
      ]
    },
    {
      "page": "cpp_multinomial_gaga",
      "title": "Fit a multinomial model via the GAGA algorithm using cpp",
      "topics": [
        "cpp_multinomial_gaga"
      ]
    },
    {
      "page": "cpp_poisson_gaga",
      "title": "Fit a poisson model via the GAGA algorithm using cpp",
      "topics": [
        "cpp_poisson_gaga"
      ]
    },
    {
      "page": "GAGAs",
      "title": "GAGAs: A package for fiting a GLM with GAGA algorithm",
      "topics": [
        "GAGAs"
      ]
    },
    {
      "page": "LM_GAGA",
      "title": "Fit a linear model via the GAGA algorithm",
      "topics": [
        "LM_GAGA"
      ]
    },
    {
      "page": "logistic_GAGA",
      "title": "Fit a logistic model via the Global Adaptive Generative Adjustment algorithm",
      "topics": [
        "logistic_GAGA"
      ]
    },
    {
      "page": "multinomial_GAGA",
      "title": "Fit a multinomial model via the GAGA algorithm",
      "topics": [
        "multinomial_GAGA"
      ]
    },
    {
      "page": "poisson_GAGA",
      "title": "Fit a Poisson model via the GAGA algorithm",
      "topics": [
        "poisson_GAGA"
      ]
    },
    {
      "page": "predict_cox_GAGA",
      "title": "Get predictions from a GAGA cox model fit object",
      "topics": [
        "predict_cox_GAGA"
      ]
    },
    {
      "page": "predict_LM_GAGA",
      "title": "Get predictions from a GAGA linear model fit object",
      "topics": [
        "predict_LM_GAGA"
      ]
    },
    {
      "page": "predict_logistic_GAGA",
      "title": "Get predictions from a GAGA logistic model fit object",
      "topics": [
        "predict_logistic_GAGA"
      ]
    },
    {
      "page": "predict_multinomial_GAGA",
      "title": "Get predictions from a GAGA multinomial model fit object",
      "topics": [
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      ]
    },
    {
      "page": "predict_poisson_GAGA",
      "title": "Get predictions from a GAGA poisson model fit object",
      "topics": [
        "predict_poisson_GAGA"
      ]
    },
    {
      "page": "predict.GAGA",
      "title": "Get predictions from a GAGA fit object",
      "topics": [
        "predict.GAGA"
      ]
    },
    {
      "page": "rcpp_lm_gaga",
      "title": "Fit a linear model via the GAGA algorithm using cpp.",
      "topics": [
        "rcpp_lm_gaga"
      ]
    },
    {
      "page": "summary.GAGA",
      "title": "Print a summary of GAGA object",
      "topics": [
        "summary.GAGA"
      ]
    }
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