{
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  "Title": "The Knockoff Filter for Controlled Variable Selection",
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  "Date": "2022-08-12",
  "Authors@R": "c(person(\"Rina\", \"Foygel Barber\", role = c(\"ctb\"),\ncomment=\"Development of the original Fixed-X Knockoffs\"),\nperson(\"Emmanuel\", \"Candes\", role = c(\"ctb\"),\ncomment=\"Development of Model-X Knockoffs and original Fixed-X Knockoffs\"),\nperson(\"Lucas\", \"Janson\", role = c(\"ctb\"),\ncomment=\"Development of Model-X Knockoffs\"),\nperson(\"Evan\", \"Patterson\", role = c(\"aut\"),\ncomment=\"Earlier R package for the original Fixed-X Knockoffs\"),\nperson(\"Matteo\", \"Sesia\", role = c(\"aut\",\"cre\"),\ncomment=\"R package for Model-X Knockoffs\", email=\"sesia@marshall.usc.edu\"))",
  "Description": "The knockoff filter is a general procedure for controlling\nthe false discovery rate (FDR) when performing variable\nselection. For more information, see the website below and the\naccompanying paper: Candes et al., \"Panning for gold: model-X\nknockoffs for high-dimensional controlled variable selection\",\nJ. R. Statist. Soc. B (2018) 80, 3, pp. 551-577.",
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  "Author": "Rina Foygel Barber [ctb] (Development of the original Fixed-X\nKnockoffs), Emmanuel Candes [ctb] (Development of Model-X\nKnockoffs and original Fixed-X Knockoffs), Lucas Janson [ctb]\n(Development of Model-X Knockoffs), Evan Patterson [aut]\n(Earlier R package for the original Fixed-X Knockoffs), Matteo\nSesia [aut, cre] (R package for Model-X Knockoffs)",
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    "stat.sqrt_lasso",
    "stat.stability_selection"
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      "page": "knockoff",
      "title": "knockoff: A package for controlled variable selection",
      "topics": [
        "knockoff"
      ]
    },
    {
      "page": "knockoff.filter",
      "title": "The Knockoff Filter",
      "topics": [
        "knockoff.filter"
      ]
    },
    {
      "page": "knockoff.threshold",
      "title": "Threshold for the knockoff filter",
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