{
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  "Package": "CCI",
  "Type": "Package",
  "Title": "Computational Test for Conditional Independence",
  "Version": "0.3.6.1",
  "Date": "2026-03-03",
  "Authors@R": "c(person(given = \"Christian\",\nfamily = \"Thorjussen\",\nrole = c(\"aut\", \"cre\"),\nemail = \"christianbern@gmail.com\",\ncomment = c(ORCID = \"0009-0005-5006-6491\")),\nperson(given = \"Kristian Hovde\",\nfamily = \"Liland\",\nrole = c(\"aut\"),\nemail = \"kristian.liland@nmbu.no\",\ncomment = c(ORCID = \"0000-0001-6468-9423\")))",
  "Maintainer": "Christian Thorjussen <christianbern@gmail.com>",
  "Description": "Tool for performing computational testing for conditional\nindependence between variables in a dataset. 'CCI' implements\npermutation in combination with Monte Carlo Cross-Validation in\ngenerating null distributions and test statistics. For more\ndetails see Computational Test for Conditional Independence\n(2024) <doi:10.3390/a17080323>.",
  "License": "GPL (>= 2)",
  "URL": "https://github.com/khliland/CCI",
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  "Date/Publication": "2026-05-15 17:14:58 UTC",
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  "Author": "Christian Thorjussen [aut, cre] (ORCID:\n<https://orcid.org/0009-0005-5006-6491>),\nKristian Hovde Liland [aut] (ORCID:\n<https://orcid.org/0000-0001-6468-9423>)",
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  "_exports": [
    "add_interaction_terms",
    "add_poly_terms",
    "build_formula",
    "CCI.direction",
    "CCI.pretuner",
    "CCI.test",
    "check_formula",
    "clean_formula",
    "get_pvalues",
    "get_tuned_params",
    "is_categorical_Z_any",
    "make_strata_from_categorical_Z",
    "perm.test",
    "permute_within_strata",
    "QQplot",
    "test.gen",
    "unclean_formula",
    "wrapper_knn",
    "wrapper_ranger",
    "wrapper_svm",
    "wrapper_xgboost"
  ],
  "_datasets": [
    {
      "name": "ExponentialNoise",
      "title": "Example dataset: ExponentialNoise",
      "object": "ExponentialNoise",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Z1",
        "Z2",
        "X",
        "Y"
      ],
      "rows": 1000,
      "table": true,
      "tojson": true
    },
    {
      "name": "HardCase",
      "title": "Example dataset: HardCase",
      "object": "HardCase",
      "class": [
        "data.frame"
      ],
      "fields": [
        "X",
        "Y",
        "Z1",
        "Z2"
      ],
      "rows": 500,
      "table": true,
      "tojson": true
    },
    {
      "name": "NonLinearCategorization",
      "title": "Example dataset: NonLinearCategorization",
      "object": "NonLinearCategorization",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Z",
        "X",
        "Y"
      ],
      "rows": 600,
      "table": true,
      "tojson": true
    },
    {
      "name": "NonLinNormal",
      "title": "Example dataset: NonLinNormal",
      "object": "NonLinNormal",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Z1",
        "Z2",
        "X",
        "Y"
      ],
      "rows": 500,
      "table": true,
      "tojson": true
    },
    {
      "name": "NonLinNormalZs_d0",
      "title": "Example dataset: NonLinNormalZs_d0",
      "object": "NonLinNormalZs_d0",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Z1",
        "Z2",
        "Z3",
        "Z4",
        "Z5",
        "Z6",
        "Z7",
        "Z8",
        "Z9",
        "Z10",
        "Z11",
        "Z12",
        "Z13",
        "Z14",
        "Z15",
        "X",
        "Y"
      ],
      "rows": 1000,
      "table": true,
      "tojson": true
    },
    {
      "name": "NonLinNormalZs_d05",
      "title": "Example dataset: NonLinNormalZs_d05",
      "object": "NonLinNormalZs_d05",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Z1",
        "Z2",
        "Z3",
        "Z4",
        "Z5",
        "Z6",
        "Z7",
        "Z8",
        "Z9",
        "Z10",
        "Z11",
        "Z12",
        "Z13",
        "Z14",
        "Z15",
        "X",
        "Y"
      ],
      "rows": 1000,
      "table": true,
      "tojson": true
    },
    {
      "name": "NormalData",
      "title": "Example dataset: NormalData",
      "object": "NormalData",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Z1",
        "Z2",
        "X",
        "Y"
      ],
      "rows": 400,
      "table": true,
      "tojson": true
    },
    {
      "name": "PoissonNoise",
      "title": "Example dataset: PoissonNoise",
      "object": "PoissonNoise",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Z1",
        "Z2",
        "X",
        "Y"
      ],
      "rows": 1000,
      "table": true,
      "tojson": true
    },
    {
      "name": "PolyData",
      "title": "Example dataset: PolyData",
      "object": "PolyData",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Z1",
        "Z2",
        "X",
        "Y"
      ],
      "rows": 600,
      "table": true,
      "tojson": true
    },
    {
      "name": "UniformNoise_large",
      "title": "Example dataset: UniformNoise_large",
      "object": "UniformNoise_large",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Z1",
        "Z2",
        "X",
        "Y"
      ],
      "rows": 20000,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "add_interaction_terms",
      "title": "Creates interaction terms for specified variables in a data frame Interaction terms are named as '<var1>_int_<var2>' (e.g., 'Z1_int_Z2' for the product of 'Z1' and 'Z2').",
      "topics": [
        "add_interaction_terms"
      ]
    },
    {
      "page": "add_poly_terms",
      "title": "Creates polynomial terms for specified variables in a data frame Polynomial terms are named as '<variable>_d_<degree>' (e.g., 'Z1_d_2' for the square of 'Z1').",
      "topics": [
        "add_poly_terms"
      ]
    },
    {
      "page": "build_formula",
      "title": "Build an expanded formula with poly and interaction terms",
      "topics": [
        "build_formula"
      ]
    },
    {
      "page": "CCI.direction",
      "title": "Choose Direction for testing for the CCI test",
      "topics": [
        "CCI.direction"
      ]
    },
    {
      "page": "CCI.pretuner",
      "title": "CCI tuner function for CCI test",
      "topics": [
        "CCI.pretuner",
        "tuner"
      ]
    },
    {
      "page": "CCI.test",
      "title": "Computational test for conditional independence based on ML and Monte Carlo Cross Validation",
      "topics": [
        "CCI",
        "CCI.test"
      ]
    },
    {
      "page": "check_formula",
      "title": "Check the formula statement",
      "topics": [
        "check_formula"
      ]
    },
    {
      "page": "clean_formula",
      "title": "Clean and Reformat Formula String",
      "topics": [
        "clean_formula"
      ]
    },
    {
      "page": "ExponentialNoise",
      "title": "Example dataset: ExponentialNoise",
      "topics": [
        "ExponentialNoise"
      ]
    },
    {
      "page": "get_pvalues",
      "title": "P-value Calculation Based on Null Distribution and Test Statistic",
      "topics": [
        "get_pvalues"
      ]
    },
    {
      "page": "get_tuned_params",
      "title": "Get the best parameters after tuning with CCI.tuner",
      "topics": [
        "get_tuned_params"
      ]
    },
    {
      "page": "HardCase",
      "title": "Example dataset: HardCase",
      "topics": [
        "HardCase"
      ]
    },
    {
      "page": "is_categorical_Z_any",
      "title": "Check whether Z contains at least one categorical variable",
      "topics": [
        "is_categorical_Z_any"
      ]
    },
    {
      "page": "make_strata_from_categorical_Z",
      "title": "Create strata from the categorical subset of Z",
      "topics": [
        "make_strata_from_categorical_Z"
      ]
    },
    {
      "page": "NonLinearCategorization",
      "title": "Example dataset: NonLinearCategorization",
      "topics": [
        "NonLinearCategorization"
      ]
    },
    {
      "page": "NonLinNormal",
      "title": "Example dataset: NonLinNormal",
      "topics": [
        "NonLinNormal"
      ]
    },
    {
      "page": "NonLinNormalZs_d0",
      "title": "Example dataset: NonLinNormalZs_d0",
      "topics": [
        "NonLinNormalZs_d0"
      ]
    },
    {
      "page": "NonLinNormalZs_d05",
      "title": "Example dataset: NonLinNormalZs_d05",
      "topics": [
        "NonLinNormalZs_d05"
      ]
    },
    {
      "page": "NormalData",
      "title": "Example dataset: NormalData",
      "topics": [
        "NormalData"
      ]
    },
    {
      "page": "perm.test",
      "title": "Permutation Test for Conditional Independence",
      "topics": [
        "perm.test"
      ]
    },
    {
      "page": "permute_within_strata",
      "title": "Stratified permutation of x within strata",
      "topics": [
        "permute_within_strata"
      ]
    },
    {
      "page": "plot.CCI",
      "title": "Plot for CCI testing",
      "topics": [
        "plot.CCI"
      ]
    },
    {
      "page": "PoissonNoise",
      "title": "Example dataset: PoissonNoise",
      "topics": [
        "PoissonNoise"
      ]
    },
    {
      "page": "PolyData",
      "title": "Example dataset: PolyData",
      "topics": [
        "PolyData"
      ]
    },
    {
      "page": "reports",
      "title": "Print and summary methods for the CCI class",
      "topics": [
        "print.CCI",
        "print.summary.CCI",
        "reports",
        "summary.CCI"
      ]
    },
    {
      "page": "QQplot",
      "title": "QQ-plot for multiple testing in CCI",
      "topics": [
        "QQplot"
      ]
    },
    {
      "page": "test.gen",
      "title": "Generate the Test Statistic or Null Distribution Using Permutation",
      "topics": [
        "test.gen"
      ]
    },
    {
      "page": "unclean_formula",
      "title": "Convert CI-style formula Y ~ X | Z into regression-style Y ~ X + Z",
      "topics": [
        "unclean_formula"
      ]
    },
    {
      "page": "UniformNoise_large",
      "title": "Example dataset: UniformNoise_large",
      "topics": [
        "UniformNoise_large"
      ]
    },
    {
      "page": "wrapper_knn",
      "title": "k-Nearest Neighbors (KNN) wrapper for CCI (kknn-based)",
      "topics": [
        "wrapper_knn"
      ]
    },
    {
      "page": "wrapper_ranger",
      "title": "Random Forest wrapper for CCI",
      "topics": [
        "wrapper_ranger"
      ]
    },
    {
      "page": "wrapper_svm",
      "title": "SVM wrapper for CCI",
      "topics": [
        "wrapper_svm"
      ]
    },
    {
      "page": "wrapper_xgboost",
      "title": "Extreme Gradient Boosting wrapper for CCI",
      "topics": [
        "wrapper_xgboost"
      ]
    }
  ],
  "_readme": "https://github.com/khliland/cci/raw/HEAD/README.md",
  "_rundeps": [
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    "xgboost"
  ],
  "_vignettes": [
    {
      "source": "Testing-CI-with-CCI.Rmd",
      "filename": "Testing-CI-with-CCI.html",
      "title": "Conditional Independence Testing with CCI",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Introduction",
        "how to run a basic conditional independence test using CCI",
        "Visualizing the null distribution",
        "CCI in large samples",
        "Adapting to outcome type",
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