{
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  "Package": "rFSA",
  "Type": "Package",
  "Title": "Feasible Solution Algorithm for Finding Best Subsets and\nInteractions",
  "Version": "0.9.6",
  "Date": "2020-06-10",
  "Authors@R": "c(\nperson(given=\"Joshua\",family=\"Lambert\",email=\"joshua.lambert@uc.edu\",role=c(\"aut\",\"cre\")),\nperson(given=\"Liyu\",family=\"Gong\",email=\"liyu.gong@uky.edu\",role=\"aut\"),\nperson(given=\"Corrine\",family=\"Elliott\",email=\"cfelliott@berkeley.edu\",role=\"aut\"),\nperson(given=\"Sarah\",family=\"Janse\",email=\"Sarah.Janse@osumc.edu\",role=\"ctb\"))",
  "Description": "Assists in statistical model building to find optimal and\nsemi-optimal higher order interactions and best subsets. Uses\nthe lm(), glm(), and other R functions to fit models generated\nfrom a feasible solution algorithm. Discussed in Subset\nSelection in Regression, A Miller (2002). Applied and explained\nfor least median of squares in Hawkins (1993)\n<doi:10.1016/0167-9473(93)90246-P>. The feasible solution\nalgorithm comes up with model forms of a specific type that can\nhave fixed variables, higher order interactions and their lower\norder terms.",
  "License": "GPL-2",
  "RoxygenNote": "7.1.0",
  "Config/pak/sysreqs": "cmake libglpk-dev make libicu-dev libxml2-dev",
  "Repository": "https://joshuawlambert.r-universe.dev",
  "Date/Publication": "2021-06-30 16:49:59 UTC",
  "RemoteUrl": "https://github.com/joshuawlambert/rfsa",
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    "User": "root"
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  "Author": "Joshua Lambert [aut, cre],\nLiyu Gong [aut],\nCorrine Elliott [aut],\nSarah Janse [ctb]",
  "Maintainer": "Joshua Lambert <joshua.lambert@uc.edu>",
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    "author": "Joshua Lambert <joshua.lambert@uc.edu>",
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    "message": "added functionality \n\nvar4int now supports more than one variable.",
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  "_updates": [],
  "_tags": [],
  "_topics": [
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    "fsa",
    "interaction",
    "models",
    "parallel",
    "statistical",
    "statistics",
    "subset"
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      "date": "2018-01-10"
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    "glmFSA",
    "int.p.val",
    "list.criterion",
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      "page": "adj.r.squared",
      "title": "An rFSA Criterion Function.",
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      ]
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    {
      "page": "apress",
      "title": "An rFSA Criterion Function.",
      "topics": [
        "apress"
      ]
    },
    {
      "page": "bdist",
      "title": "An rFSA Criterion Function.",
      "topics": [
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      ]
    },
    {
      "page": "fitmodels",
      "title": "Model fitting function for FSA solutions",
      "topics": [
        "fitmodels"
      ]
    },
    {
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      "title": "Fitted Values for FSA solutions",
      "topics": [
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      ]
    },
    {
      "page": "FSA",
      "title": "FSA: Feasible Solution Algorithm",
      "topics": [
        "FSA",
        "glmFSA",
        "lmFSA"
      ]
    },
    {
      "page": "int.p.val",
      "title": "An rFSA Criterion Function.",
      "topics": [
        "int.p.val"
      ]
    },
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      "title": "List all included Criteria function for lmFSA and glmFSA.",
      "topics": [
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      ]
    },
    {
      "page": "max_abs_resid",
      "title": "Return maximum absolute residual from a model",
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      ]
    },
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      "page": "nextswap",
      "title": "Variables to include in the >1st step of an mth order interaction model determined from the Feasible Soution Alorithm.",
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      ]
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      "page": "pFSA",
      "title": "pFSA: Pareto Feasible Solution Algorithm",
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      ]
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      "title": "Diagnostic Plots for FSA solutions",
      "topics": [
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    },
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      "title": "Printing function for FSA solutions",
      "topics": [
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      ]
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      "title": "Return QICu for geepack::geeglm",
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      ]
    },
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      "title": "An rFSA Criterion Function.",
      "topics": [
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      ]
    },
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      "title": "An rFSA Criterion Function.",
      "topics": [
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