{
  "_id": "6a1bf0911d7bb097a0a22d20",
  "Package": "eat",
  "Title": "Efficiency Analysis Trees",
  "Version": "0.1.2",
  "Authors@R": "c(\nperson(given = \"Miriam\",\nfamily = \"Esteve\",\nrole = c(\"cre\", \"aut\"),\nemail = \"mestevecampello@gmail.com\",\ncomment = c(ORCID = \"0000-0002-5908-0581\")),\nperson(given = \"Víctor\",\nfamily = \"España\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-1807-6180\")),\nperson(given = \"Juan\",\nfamily = \"Aparicio\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0002-0867-0004\")),\nperson(given = \"Xavier\",\nfamily = \"Barber\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0003-3079-5855\"))\n)",
  "Description": "Functions are provided to determine production frontiers\nand technical efficiency measures through non-parametric\ntechniques based upon regression trees. The package includes\ncode for estimating radial input, output, directional and\nadditive measures, plotting graphical representations of the\nscores and the production frontiers by means of trees, and\ndetermining rankings of importance of input variables in the\nanalysis. Additionally, an adaptation of Random Forest by a set\nof individual Efficiency Analysis Trees for estimating\ntechnical efficiency is also included. More details in:\n<doi:10.1016/j.eswa.2020.113783>.",
  "License": "GPL-3",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RoxygenNote": "7.1.2",
  "RdMacros": "Rdpack",
  "VignetteBuilder": "knitr",
  "URL": "https://efficiencytools.wordpress.com/",
  "BugReports": "https://github.com/MiriamEsteve/EAT/issues",
  "Config/pak/sysreqs": "libicu-dev",
  "Repository": "https://miriamesteve.r-universe.dev",
  "Date/Publication": "2022-01-16 12:04:03 UTC",
  "RemoteUrl": "https://github.com/miriamesteve/eat",
  "RemoteRef": "HEAD",
  "RemoteSha": "94543714b79368b724d62f0564c02b075ca29a1b",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-31 08:08:00 UTC",
    "User": "root"
  },
  "Author": "Miriam Esteve [cre, aut] (ORCID:\n<https://orcid.org/0000-0002-5908-0581>),\nVíctor España [aut] (ORCID: <https://orcid.org/0000-0002-1807-6180>),\nJuan Aparicio [aut] (ORCID: <https://orcid.org/0000-0002-0867-0004>),\nXavier Barber [aut] (ORCID: <https://orcid.org/0000-0003-3079-5855>)",
  "Maintainer": "Miriam Esteve <mestevecampello@gmail.com>",
  "MD5sum": "792c8aa262bafb089eb72bf11cd92690",
  "_user": "miriamesteve",
  "_type": "src",
  "_file": "eat_0.1.2.tar.gz",
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  "_sha256": "2093df03d5a2bda23e5c8e3ba2d584b6aae76832836f4378cdf3d38c1bef62b1",
  "_created": "2026-05-31T08:08:00.000Z",
  "_published": "2026-05-31T08:25:53.205Z",
  "_distro": "noble",
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      "package": "utils",
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  "_owner": "miriamesteve",
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  "_updates": [],
  "_tags": [],
  "_stars": 6,
  "_contributors": [
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  "_devurl": "https://github.com/miriamesteve/eat",
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  "_rbuild": "4.6.0",
  "_assets": [
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    "extra/citation.json",
    "extra/citation.txt",
    "extra/contents.json",
    "extra/eat.html",
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    "extra/readme.md",
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  "_homeurl": "https://github.com/miriamesteve/eat",
  "_realowner": "miriamesteve",
  "_cranurl": true,
  "_releases": [
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      "date": "2021-04-09"
    },
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      "version": "0.1.1",
      "date": "2022-01-14"
    },
    {
      "version": "0.1.2",
      "date": "2022-01-16"
    },
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      "version": "0.1.3",
      "date": "2022-08-15"
    },
    {
      "version": "0.1.4",
      "date": "2023-01-14"
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  ],
  "_exports": [
    "bestEAT",
    "bestRFEAT",
    "EAT",
    "EAT_frontier_levels",
    "EAT_leaf_stats",
    "EAT_size",
    "efficiencyCEAT",
    "efficiencyDensity",
    "efficiencyEAT",
    "efficiencyJitter",
    "efficiencyRFEAT",
    "frontier",
    "plotEAT",
    "plotRFEAT",
    "rankingEAT",
    "rankingRFEAT",
    "RFEAT",
    "X2Y2.sim",
    "Y1.sim"
  ],
  "_datasets": [
    {
      "name": "PISAindex",
      "title": "PISA score and social index by country",
      "object": "PISAindex",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Country",
        "Continent",
        "S_PISA",
        "R_PISA",
        "M_PISA",
        "NBMC",
        "WS",
        "S",
        "PS",
        "ABK",
        "AIC",
        "HW",
        "EQ",
        "PR",
        "PFC",
        "I",
        "AAE",
        "GDP_PPP"
      ],
      "rows": 72,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "alpha",
      "title": "Alpha Calculation for Pruning Procedure of Efficiency Analysis Trees",
      "topics": [
        "alpha"
      ]
    },
    {
      "page": "bagging",
      "title": "Bagging data",
      "topics": [
        "bagging"
      ]
    },
    {
      "page": "barplot_importance",
      "title": "Barplot Variable Importance",
      "topics": [
        "barplot_importance"
      ]
    },
    {
      "page": "bestEAT",
      "title": "Tuning an Efficiency Analysis Trees model",
      "topics": [
        "bestEAT"
      ]
    },
    {
      "page": "bestRFEAT",
      "title": "Tuning a Random Forest + Efficiency Analysis Trees model",
      "topics": [
        "bestRFEAT"
      ]
    },
    {
      "page": "CEAT_BCC_in",
      "title": "Banker, Charnes and Cooper programming model with input orientation for a Convexified Efficiency Analysis Trees model",
      "topics": [
        "CEAT_BCC_in"
      ]
    },
    {
      "page": "CEAT_BCC_out",
      "title": "Banker, Charnes and Cooper programming model with output orientation for a Convexified Efficiency Analysis Trees model",
      "topics": [
        "CEAT_BCC_out"
      ]
    },
    {
      "page": "CEAT_DDF",
      "title": "Directional Distance Function mathematical programming model for a Convexified Efficiency Analysis Trees model",
      "topics": [
        "CEAT_DDF"
      ]
    },
    {
      "page": "CEAT_RSL_in",
      "title": "Russell Model with input orientation for a Convexified Efficiency Analysis Trees model",
      "topics": [
        "CEAT_RSL_in"
      ]
    },
    {
      "page": "CEAT_RSL_out",
      "title": "Russell Model with output orientation for a Convexified Efficiency Analysis Trees model",
      "topics": [
        "CEAT_RSL_out"
      ]
    },
    {
      "page": "CEAT_WAM",
      "title": "Weighted Additive Model for a Convexified Efficiency Analysis Trees model",
      "topics": [
        "CEAT_WAM"
      ]
    },
    {
      "page": "checkEAT",
      "title": "Check Efficiency Analysis Trees.",
      "topics": [
        "checkEAT"
      ]
    },
    {
      "page": "comparePareto",
      "title": "Pareto-dominance relationships",
      "topics": [
        "comparePareto"
      ]
    },
    {
      "page": "deepEAT",
      "title": "Deep Efficiency Analysis Trees",
      "topics": [
        "deepEAT"
      ]
    },
    {
      "page": "EAT",
      "title": "Efficiency Analysis Trees",
      "topics": [
        "EAT"
      ]
    },
    {
      "page": "EAT_BCC_in",
      "title": "Banker, Charnes and Cooper Programming Model with Input Orientation for an Efficiency Analysis Trees model",
      "topics": [
        "EAT_BCC_in"
      ]
    },
    {
      "page": "EAT_BCC_out",
      "title": "Banker, Charnes and Cooper Programming Model with Output Orientation for an Efficiency Analysis Trees model",
      "topics": [
        "EAT_BCC_out"
      ]
    },
    {
      "page": "EAT_DDF",
      "title": "Directional Distance Function Programming Model for an Efficiency Analysis Trees model",
      "topics": [
        "EAT_DDF"
      ]
    },
    {
      "page": "EAT_frontier_levels",
      "title": "Output Levels in an Efficiency Analysis Trees model",
      "topics": [
        "EAT_frontier_levels"
      ]
    },
    {
      "page": "EAT_leaf_stats",
      "title": "Descriptive Summary Statistics Table for the Leaf Nodes of an Efficiency Analysis Trees model",
      "topics": [
        "EAT_leaf_stats"
      ]
    },
    {
      "page": "EAT_object",
      "title": "Create a EAT object",
      "topics": [
        "EAT_object"
      ]
    },
    {
      "page": "EAT_RSL_in",
      "title": "Russell Model with Input Orientation for an Efficiency Analysis Trees model",
      "topics": [
        "EAT_RSL_in"
      ]
    },
    {
      "page": "EAT_RSL_out",
      "title": "Russell Model with Output Orientation for an Efficiency Analysis Trees model",
      "topics": [
        "EAT_RSL_out"
      ]
    },
    {
      "page": "EAT_size",
      "title": "Number of Leaf Nodes in an Efficiency Analysis Trees model",
      "topics": [
        "EAT_size"
      ]
    },
    {
      "page": "EAT_WAM",
      "title": "Weighted Additive Model for an Efficiency Analysis Trees model",
      "topics": [
        "EAT_WAM"
      ]
    },
    {
      "page": "efficiencyCEAT",
      "title": "Efficiency Scores computed through a Convexified Efficiency Analysis Trees model.",
      "topics": [
        "efficiencyCEAT"
      ]
    },
    {
      "page": "efficiencyDensity",
      "title": "Efficiency Scores Density Plot",
      "topics": [
        "efficiencyDensity"
      ]
    },
    {
      "page": "efficiencyEAT",
      "title": "Efficiency Scores computed through an Efficiency Analysis Trees model.",
      "topics": [
        "efficiencyEAT"
      ]
    },
    {
      "page": "efficiencyJitter",
      "title": "Efficiency Scores Jitter Plot",
      "topics": [
        "efficiencyJitter"
      ]
    },
    {
      "page": "efficiencyRFEAT",
      "title": "Efficiency Scores computed through a Random Forest + Efficiency Analysis Trees model.",
      "topics": [
        "efficiencyRFEAT"
      ]
    },
    {
      "page": "estimEAT",
      "title": "Estimation of child nodes",
      "topics": [
        "estimEAT"
      ]
    },
    {
      "page": "frontier",
      "title": "Efficiency Analysis Trees Frontier Graph",
      "topics": [
        "frontier"
      ]
    },
    {
      "page": "generateLv",
      "title": "Train and Test Sets Generation",
      "topics": [
        "generateLv"
      ]
    },
    {
      "page": "imp_var_EAT",
      "title": "Breiman's Variable Importance",
      "topics": [
        "imp_var_EAT"
      ]
    },
    {
      "page": "imp_var_RFEAT",
      "title": "Variable Importance through Random Forest + Efficiency Analysis Trees",
      "topics": [
        "imp_var_RFEAT"
      ]
    },
    {
      "page": "isFinalNode",
      "title": "Is Final Node",
      "topics": [
        "isFinalNode"
      ]
    },
    {
      "page": "layout",
      "title": "Layout for nodes in plotEAT",
      "topics": [
        "layout"
      ]
    },
    {
      "page": "M_Breiman",
      "title": "Breiman Importance",
      "topics": [
        "M_Breiman"
      ]
    },
    {
      "page": "mse",
      "title": "Mean Squared Error",
      "topics": [
        "mse"
      ]
    },
    {
      "page": "mtry_inputSelection",
      "title": "Random Selection of Variables",
      "topics": [
        "mtry_inputSelection"
      ]
    },
    {
      "page": "PISAindex",
      "title": "PISA score and social index by country",
      "topics": [
        "PISAindex"
      ]
    },
    {
      "page": "plotEAT",
      "title": "Efficiency Analysis Trees Plot",
      "topics": [
        "plotEAT"
      ]
    },
    {
      "page": "plotRFEAT",
      "title": "Random Forest + Efficiency Analysis Trees Plot",
      "topics": [
        "plotRFEAT"
      ]
    },
    {
      "page": "posIdNode",
      "title": "Position of the node",
      "topics": [
        "posIdNode"
      ]
    },
    {
      "page": "predict.EAT",
      "title": "Model Prediction for Efficiency Analysis Trees.",
      "topics": [
        "predict.EAT"
      ]
    },
    {
      "page": "predict.RFEAT",
      "title": "Model prediction for Random Forest + Efficiency Analysis Trees model.",
      "topics": [
        "predict.RFEAT"
      ]
    },
    {
      "page": "predictFDH",
      "title": "Model prediction for Free Disposal Hull",
      "topics": [
        "predictFDH"
      ]
    },
    {
      "page": "predictor",
      "title": "Efficiency Analysis Trees Predictor",
      "topics": [
        "predictor"
      ]
    },
    {
      "page": "preProcess",
      "title": "Data Preprocessing for Efficiency Analysis Trees",
      "topics": [
        "preProcess"
      ]
    },
    {
      "page": "RandomEAT",
      "title": "Individual EAT for Random Forest",
      "topics": [
        "RandomEAT"
      ]
    },
    {
      "page": "rankingEAT",
      "title": "Ranking of Variables by Efficiency Analysis Trees model.",
      "topics": [
        "rankingEAT"
      ]
    },
    {
      "page": "rankingRFEAT",
      "title": "Ranking of variables by Random Forest + Efficiency Analysis Trees model.",
      "topics": [
        "rankingRFEAT"
      ]
    },
    {
      "page": "RBranch",
      "title": "Branch Pruning",
      "topics": [
        "RBranch"
      ]
    },
    {
      "page": "RCV",
      "title": "RCV",
      "topics": [
        "RCV"
      ]
    },
    {
      "page": "RF_predictor",
      "title": "Random Forest + Efficiency Analysis Trees Predictor",
      "topics": [
        "RF_predictor"
      ]
    },
    {
      "page": "RFEAT",
      "title": "Random Forest + Efficiency Analysis Trees",
      "topics": [
        "RFEAT"
      ]
    },
    {
      "page": "RFEAT_object",
      "title": "Create a RFEAT object",
      "topics": [
        "RFEAT_object"
      ]
    },
    {
      "page": "scores",
      "title": "Pruning Scores",
      "topics": [
        "scores"
      ]
    },
    {
      "page": "select_mtry",
      "title": "Select Possible Inputs in Split.",
      "topics": [
        "select_mtry"
      ]
    },
    {
      "page": "selectTk",
      "title": "Select Tk",
      "topics": [
        "selectTk"
      ]
    },
    {
      "page": "SERules",
      "title": "SERules",
      "topics": [
        "SERules"
      ]
    },
    {
      "page": "split",
      "title": "Split node",
      "topics": [
        "split"
      ]
    },
    {
      "page": "split_forest",
      "title": "Split Node in Random Forest EAT",
      "topics": [
        "split_forest"
      ]
    },
    {
      "page": "treesForRCV",
      "title": "Trees for RCV",
      "topics": [
        "treesForRCV"
      ]
    },
    {
      "page": "X2Y2.sim",
      "title": "2 Inputs & 2 Outputs Data Generation",
      "topics": [
        "X2Y2.sim"
      ]
    },
    {
      "page": "Y1.sim",
      "title": "Single Output Data Generation",
      "topics": [
        "Y1.sim"
      ]
    }
  ],
  "_readme": "https://github.com/miriamesteve/eat/raw/HEAD/README.md",
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  "_vignettes": [
    {
      "source": "EAT.Rmd",
      "filename": "EAT.html",
      "title": "eat: Efficiency Analysis Trees",
      "author": "Center of Operations Research",
      "engine": "knitr::rmarkdown",
      "headings": [
        "A brief introduction to production theory field",
        "Summary of eat functions",
        "The PISAindex database",
        "Modeling a scenario with an input and an output. Plotting the frontier",
        "EAT()",
        "Categorical variables",
        "frontier()",
        "Modeling a multioutput scenario. Feature selection.",
        "rankingEAT()",
        "Graphical representation by a tree structure",
        "plotEAT()",
        "The EAT hyperparameter tuning",
        "bestEAT()",
        "Efficiency scores. Graphical representation.",
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