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  "Title": "Depth-Based Classification and Calculation of Data Depth",
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  "Date": "2024-09-29",
  "Authors@R": "c(person(\"Oleksii\", \"Pokotylo\", role=c(\"aut\", \"cre\"),\nemail = \"alexey.pokotylo@gmail.com\"),\nperson(\"Pavlo\", \"Mozharovskyi\", role=c(\"aut\"),\nemail = \"pavlo.mozharovskyi@telecom-paris.fr\"),\nperson(\"Rainer\", \"Dyckerhoff\", role=c(\"aut\"),\nemail = \"rainer.dyckerhoff@statistik.uni-koeln.de\"),\nperson(\"Stanislav\", \"Nagy\", role=c(\"aut\"),\nemail = \"nagy@karlin.mff.cuni.cz\"))",
  "Description": "Contains procedures for depth-based supervised learning,\nwhich are entirely non-parametric, in particular the\nDDalpha-procedure (Lange, Mosler and Mozharovskyi, 2014\n<doi:10.1007/s00362-012-0488-4>). The training data sample is\ntransformed by a statistical depth function to a compact\nlow-dimensional space, where the final classification is done.\nIt also offers an extension to functional data and routines for\ncalculating certain notions of statistical depth functions. 50\nmultivariate and 5 functional classification problems are\nincluded. (Pokotylo, Mozharovskyi and Dyckerhoff, 2019\n<doi:10.18637/jss.v091.i05>).",
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      "name": "geneexp",
      "title": "Gene Expression Profile Data",
      "object": "geneexp",
      "file": "geneexp.rda",
      "class": [
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      "fields": [],
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    },
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      "name": "glass",
      "title": "Data for Classification",
      "object": "glass",
      "file": "glass.txt.gz",
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        "Mg",
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        "Si",
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      "table": true,
      "tojson": true
    },
    {
      "name": "groessen_MvsF",
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      "object": "groessen_MvsF",
      "file": "groessen_MvsF.txt.gz",
      "class": [
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      "fields": [
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        "father",
        "sex"
      ],
      "rows": 230,
      "table": true,
      "tojson": true
    },
    {
      "name": "growth",
      "title": "Berkeley Growth Study Data",
      "object": "growth",
      "file": "growth.rda",
      "class": [
        "functional"
      ],
      "fields": [],
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      "tojson": false
    },
    {
      "name": "haberman",
      "title": "Data for Classification",
      "object": "haberman",
      "file": "haberman.txt.gz",
      "class": [
        "data.frame"
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      "fields": [
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      ],
      "rows": 306,
      "table": true,
      "tojson": true
    },
    {
      "name": "heart",
      "title": "Data for Classification",
      "object": "heart",
      "file": "heart.txt.gz",
      "class": [
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        "X4",
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        "X12",
        "X13",
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      "rows": 270,
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      "tojson": true
    },
    {
      "name": "hemophilia",
      "title": "Data for Classification",
      "object": "hemophilia",
      "file": "hemophilia.txt.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
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        "AHFactivity.1",
        "gr"
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      "table": true,
      "tojson": true
    },
    {
      "name": "indian_liver_patient_1vs2",
      "title": "Data for Classification",
      "object": "indian_liver_patient_1vs2",
      "file": "indian_liver_patient_1vs2.txt.gz",
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      ],
      "rows": 579,
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      "tojson": true
    },
    {
      "name": "indian_liver_patient_FvsM",
      "title": "Data for Classification",
      "object": "indian_liver_patient_FvsM",
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      "rows": 579,
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      "tojson": true
    },
    {
      "name": "iris_setosavsversicolor",
      "title": "Data for Classification",
      "object": "iris_setosavsversicolor",
      "file": "iris_setosavsversicolor.txt.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
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        "X3",
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      "rows": 100,
      "table": true,
      "tojson": true
    },
    {
      "name": "iris_setosavsvirginica",
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      "object": "iris_setosavsvirginica",
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    {
      "name": "iris_versicolorvsvirginica",
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      "object": "iris_versicolorvsvirginica",
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      "class": [
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      "fields": [
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    },
    {
      "name": "irish_ed_MvsF",
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      "object": "irish_ed_MvsF",
      "file": "irish_ed_MvsF.txt.gz",
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      "rows": 500,
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      "tojson": true
    },
    {
      "name": "kidney",
      "title": "Data for Classification",
      "object": "kidney",
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        "sex",
        "disease",
        "C"
      ],
      "rows": 76,
      "table": true,
      "tojson": true
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    {
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      "title": "Relationship of Age Patterns of Fecundity to Mortality for Female Medflies.",
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      "file": "medflies.rda",
      "class": [
        "functional"
      ],
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      "tojson": false
    },
    {
      "name": "pima",
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      "object": "pima",
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        "C"
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      "rows": 200,
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    },
    {
      "name": "plasma_retinol_MvsF",
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      "object": "plasma_retinol_MvsF",
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        "BETADIET",
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        "BETAPLASMA",
        "RETPLASMA",
        "SEX"
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      "rows": 315,
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    },
    {
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      "object": "population",
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        "functional"
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    {
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      "object": "segmentation",
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        "X9",
        "X10",
        "C"
      ],
      "rows": 660,
      "table": true,
      "tojson": true
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    {
      "name": "socmob_IvsNI",
      "title": "Data for Classification",
      "object": "socmob_IvsNI",
      "file": "socmob_IvsNI.txt.gz",
      "class": [
        "data.frame"
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      "fields": [
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        "X3",
        "X4",
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    {
      "name": "socmob_WvsB",
      "title": "Data for Classification",
      "object": "socmob_WvsB",
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      "class": [
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      "fields": [
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        "X4",
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      "tojson": true
    },
    {
      "name": "tae",
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      "object": "tae",
      "file": "tae.txt.gz",
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        "data.frame"
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        "C"
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      "rows": 151,
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      "tojson": true
    },
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      "name": "tecator",
      "title": "Functional Data Set Spectrometric Data (Tecator)",
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      "object": "tennis_MvsF",
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        "X10",
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        "X12",
        "X13",
        "X14",
        "X15",
        "C"
      ],
      "rows": 87,
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    },
    {
      "name": "tips_DvsN",
      "title": "Data for Classification",
      "object": "tips_DvsN",
      "file": "tips_DvsN.txt.gz",
      "class": [
        "data.frame"
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      "fields": [
        "TOTBILL",
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        "SEX",
        "SMOKER",
        "DAY",
        "SIZE",
        "TIME"
      ],
      "rows": 244,
      "table": true,
      "tojson": true
    },
    {
      "name": "tips_MvsF",
      "title": "Data for Classification",
      "object": "tips_MvsF",
      "file": "tips_MvsF.txt.gz",
      "class": [
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        "SMOKER",
        "DAY",
        "TIME",
        "SIZE",
        "SEX"
      ],
      "rows": 244,
      "table": true,
      "tojson": true
    },
    {
      "name": "uscrime_SvsN",
      "title": "Data for Classification",
      "object": "uscrime_SvsN",
      "file": "uscrime_SvsN.txt.gz",
      "class": [
        "data.frame"
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      "fields": [
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        "Ed",
        "Ex0",
        "Ex1",
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        "M",
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        "NW",
        "U1",
        "U2",
        "W",
        "X",
        "S"
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      "rows": 47,
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      "tojson": true
    },
    {
      "name": "vertebral_column",
      "title": "Data for Classification",
      "object": "vertebral_column",
      "file": "vertebral_column.txt.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
        "X1",
        "X2",
        "X3",
        "X4",
        "X5",
        "X6",
        "C"
      ],
      "rows": 310,
      "table": true,
      "tojson": true
    },
    {
      "name": "veteran_lung_cancer",
      "title": "Data for Classification",
      "object": "veteran_lung_cancer",
      "file": "veteran_lung_cancer.txt.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Celltype",
        "Survival",
        "Status",
        "Karnofsky_score",
        "Months",
        "Age",
        "Prior_therapy",
        "Treatment"
      ],
      "rows": 137,
      "table": true,
      "tojson": true
    },
    {
      "name": "vowel_MvsF",
      "title": "Data for Classification",
      "object": "vowel_MvsF",
      "file": "vowel_MvsF.txt.gz",
      "class": [
        "data.frame"
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      "fields": [
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        "X2",
        "X3",
        "X4",
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        "X6",
        "X7",
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        "X9",
        "X10",
        "X11",
        "X12",
        "X13",
        "C"
      ],
      "rows": 990,
      "table": true,
      "tojson": true
    },
    {
      "name": "wine_1vs2",
      "title": "Data for Classification",
      "object": "wine_1vs2",
      "file": "wine_1vs2.txt.gz",
      "class": [
        "data.frame"
      ],
      "fields": [
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        "X2",
        "X3",
        "X4",
        "X5",
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        "X7",
        "X8",
        "X9",
        "X10",
        "X11",
        "X12",
        "X13",
        "C"
      ],
      "rows": 130,
      "table": true,
      "tojson": true
    },
    {
      "name": "wine_1vs3",
      "title": "Data for Classification",
      "object": "wine_1vs3",
      "file": "wine_1vs3.txt.gz",
      "class": [
        "data.frame"
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      "fields": [
        "X1",
        "X2",
        "X3",
        "X4",
        "X5",
        "X6",
        "X7",
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        "X9",
        "X10",
        "X11",
        "X12",
        "X13",
        "C"
      ],
      "rows": 107,
      "table": true,
      "tojson": true
    },
    {
      "name": "wine_2vs3",
      "title": "Data for Classification",
      "object": "wine_2vs3",
      "file": "wine_2vs3.txt.gz",
      "class": [
        "data.frame"
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      "fields": [
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        "X2",
        "X3",
        "X4",
        "X5",
        "X6",
        "X7",
        "X8",
        "X9",
        "X10",
        "X11",
        "X12",
        "X13",
        "C"
      ],
      "rows": 119,
      "table": true,
      "tojson": true
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  ],
  "_help": [
    {
      "page": "ddalpha-package",
      "title": "Depth-Based Classification and Calculation of Data Depth",
      "topics": [
        "ddalpha-package",
        "ddalpha"
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    },
    {
      "page": "Cmetric",
      "title": "Fast Computation of the Uniform Metric for Sets of Functional Data",
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    },
    {
      "page": "compclassf.classify",
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        "predict.compclassf"
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    },
    {
      "page": "compclassf.train",
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    {
      "page": "CustomMethods",
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    },
    {
      "page": "dataf",
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    },
    {
      "page": "dataf.",
      "title": "Functional Data Sets",
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    {
      "page": "dataf.geneexp",
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    {
      "page": "dataf.growth",
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    {
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        "medflies"
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    },
    {
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        "population"
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    },
    {
      "page": "dataf.population2010",
      "title": "World Historical Population-by-Country Dataset (2010 Revision)",
      "topics": [
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        "population2010"
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    },
    {
      "page": "dataf.sim.1.CFF07",
      "title": "Model 1 from Cuevas et al. (2007)",
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    },
    {
      "page": "dataf.sim.2.CFF07",
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      "topics": [
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    },
    {
      "page": "dataf.tecator",
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    {
      "page": "dataf2rawfd",
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      "page": "ddalpha.classify",
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      "page": "ddalpha.getErrorRateCV",
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    {
      "page": "ddalpha.getErrorRatePart",
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        "ddalpha.getErrorRatePart"
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    {
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    {
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        "maxD",
        "outsiders",
        "polynomial"
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    {
      "page": "ddalphaf.classify",
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      "topics": [
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    },
    {
      "page": "ddalphaf.getErrorRateCV",
      "title": "Test Functional DD-Classifier",
      "topics": [
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    {
      "page": "ddalphaf.getErrorRatePart",
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      "page": "ddalphaf.test",
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    {
      "page": "ddalphaf.train",
      "title": "Functional DD-Classifier",
      "topics": [
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    },
    {
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      "topics": [
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    },
    {
      "page": "depth.betaSkeleton",
      "title": "Calculate Beta-Skeleton Depth",
      "topics": [
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    },
    {
      "page": "depth.contours",
      "title": "Depth Contours",
      "topics": [
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    },
    {
      "page": "depth.contours.ddalpha",
      "title": "Depth Contours",
      "topics": [
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    },
    {
      "page": "depth.graph",
      "title": "Depth Graph",
      "topics": [
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    },
    {
      "page": "depth.halfspace",
      "title": "Calculate Halfspace Depth",
      "topics": [
        "depth.halfspace"
      ]
    },
    {
      "page": "depth.L2",
      "title": "Calculate L2-Depth",
      "topics": [
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    },
    {
      "page": "depth.Mahalanobis",
      "title": "Calculate Mahalanobis Depth",
      "topics": [
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    },
    {
      "page": "depth.potential",
      "title": "Calculate Potential of the Data",
      "topics": [
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    },
    {
      "page": "depth.projection",
      "title": "Calculate Projection Depth",
      "topics": [
        "depth.projection"
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    },
    {
      "page": "depth.qhpeeling",
      "title": "Calculate Convex Hull Peeling Depth",
      "topics": [
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    },
    {
      "page": "depth.sample",
      "title": "Fast Depth Computation for Univariate and Bivariate Random Samples",
      "topics": [
        "depth.sample"
      ]
    },
    {
      "page": "depth.simplicial",
      "title": "Calculate Simplicial Depth",
      "topics": [
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      ]
    },
    {
      "page": "depth.simplicialVolume",
      "title": "Calculate Simplicial Volume Depth",
      "topics": [
        "depth.simplicialVolume"
      ]
    },
    {
      "page": "depth.space.",
      "title": "Calculate Depth Space using the Given Depth",
      "topics": [
        "depth.space."
      ]
    },
    {
      "page": "depth.space.halfspace",
      "title": "Calculate Depth Space using Halfspace Depth",
      "topics": [
        "depth.space.halfspace"
      ]
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