{
  "_id": "6a103583acfb0bcc41c99b20",
  "Package": "cmahalanobis",
  "Type": "Package",
  "Title": "Calculate Distance Measures for DataFrames",
  "Version": "1.0.0",
  "Date": "2025-09-13",
  "Authors@R": "person(given = \"Flavio\",\nfamily = \"Gioia\",\nrole = c(\"aut\", \"cre\"),\nemail = \"flaviogioia.fg@gmail.com\", comment = c(ORCID = \"0009-0000-0326-3840\"))",
  "Maintainer": "Flavio Gioia <flaviogioia.fg@gmail.com>",
  "Description": "It provides functions that calculate Mahalanobis distance,\nEuclidean distance, Manhattan distance, Chebyshev distance,\nHamming distance, Canberra distance, Minkowski dissimilarity\n(distance defined for p >= 1), Cosine dissimilarity,\nBhattacharyya dissimilarity, Jaccard distance, Hellinger\ndistance, Bray-Curtis dissimilarity, Sorensen-Dice\ndissimilarity between each pair of species in a list of data\nframes. These statistics are fundamental in various fields,\nsuch as cluster analysis, classification, and other\napplications of machine learning and data mining, where\nassessing similarity or dissimilarity between data is crucial.\nThe package is designed to be flexible and easily integrated\ninto data analysis workflows, providing reliable tools for\nevaluating distances in multidimensional contexts.",
  "License": "GPL-3",
  "Encoding": "UTF-8",
  "NeedsCompilation": "no",
  "RoxygenNote": "7.3.3",
  "Packaged": {
    "Date": "2026-05-12 07:20:32 UTC",
    "User": "root"
  },
  "Author": "Flavio Gioia [aut, cre] (ORCID:\n<https://orcid.org/0009-0000-0326-3840>)",
  "Config/pak/sysreqs": "libicu-dev",
  "Repository": "https://hflavio12.r-universe.dev",
  "Date/Publication": "2025-09-14 11:30:19 UTC",
  "RemoteUrl": "https://github.com/cran/cmahalanobis",
  "RemoteRef": "HEAD",
  "RemoteSha": "85693ce1aa8fa7723c57f75bc9d8545fa5cc1000",
  "MD5sum": "034a6f225540aa005d675b94123cea28",
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  "_created": "2026-05-12T07:20:32.000Z",
  "_published": "2026-05-22T10:52:50.999Z",
  "_distro": "noble",
  "_jobs": [
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    "author": "Flavio Gioia <flaviogioia.fg@gmail.com>",
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  "_assets": [
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    "extra/contents.json",
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  "_realowner": "hflavio12",
  "_cranurl": false,
  "_releases": [
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      "version": "0.1.0",
      "date": "2024-02-20"
    },
    {
      "version": "0.2.0",
      "date": "2024-05-17"
    },
    {
      "version": "0.3.0",
      "date": "2024-05-20"
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      "date": "2025-01-08"
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  ],
  "_exports": [
    "cbhattacharyya",
    "cbraycurtis",
    "ccanberra",
    "cchebyshev",
    "ccosine",
    "ceuclide",
    "chamming",
    "chellinger",
    "cjaccard",
    "cmahalanobis",
    "cmanhattan",
    "cminkowski",
    "csorensendice",
    "generate_report_cbhattacharyya",
    "generate_report_cbraycurtis",
    "generate_report_ccanberra",
    "generate_report_cchebyshev",
    "generate_report_ccosine",
    "generate_report_ceuclide",
    "generate_report_chamming",
    "generate_report_chellinger",
    "generate_report_cjaccard",
    "generate_report_cmahalanobis",
    "generate_report_cmanhattan",
    "generate_report_cminkowski",
    "generate_report_csorensendice",
    "pvaluescbatt",
    "pvaluescbrcu",
    "pvaluesccanb",
    "pvaluesccheb",
    "pvaluesccosi",
    "pvaluesceucl",
    "pvalueschamm",
    "pvalueschell",
    "pvaluescjacc",
    "pvaluescmaha",
    "pvaluescmanh",
    "pvaluescmink",
    "pvaluescsore"
  ],
  "_help": [
    {
      "page": "cbhattacharyya",
      "title": "Calculate the Bhattacharyya dissimilarities for each pair of factors or for the index.",
      "topics": [
        "cbhattacharyya"
      ]
    },
    {
      "page": "cbraycurtis",
      "title": "Calculate the Bray-Curtis dissimilarities for each pair of factors or for the index.",
      "topics": [
        "cbraycurtis"
      ]
    },
    {
      "page": "ccanberra",
      "title": "Calculate the Canberra distances for each pair of factors or for the index.",
      "topics": [
        "ccanberra"
      ]
    },
    {
      "page": "cchebyshev",
      "title": "Calculate the Chebyshev distances for each pair of factors or for the index.",
      "topics": [
        "cchebyshev"
      ]
    },
    {
      "page": "ccosine",
      "title": "Calculate the Cosine dissimilarities for each pair of factors or for the index.",
      "topics": [
        "ccosine"
      ]
    },
    {
      "page": "ceuclide",
      "title": "Calculate the Euclidean distances for each pair of factors or for the index.",
      "topics": [
        "ceuclide"
      ]
    },
    {
      "page": "chamming",
      "title": "Calculate the Hamming distances for each pair of factors or for the index.",
      "topics": [
        "chamming"
      ]
    },
    {
      "page": "chellinger",
      "title": "Calculate the Hellinger distances for each pair of factors or for the index.",
      "topics": [
        "chellinger"
      ]
    },
    {
      "page": "cjaccard",
      "title": "Calculate the Jaccard distances for each pair of factors or for the index.",
      "topics": [
        "cjaccard"
      ]
    },
    {
      "page": "cmahalanobis",
      "title": "Calculate the Mahalanobis distances for each pair of factors or for the index.",
      "topics": [
        "cmahalanobis"
      ]
    },
    {
      "page": "cmanhattan",
      "title": "Calculate the Manhattan distances for each pair of factors or for the index.",
      "topics": [
        "cmanhattan"
      ]
    },
    {
      "page": "cminkowski",
      "title": "Calculate the Minkowski distances for each pair of factors or for the index.",
      "topics": [
        "cminkowski"
      ]
    },
    {
      "page": "csorensendice",
      "title": "Calculate the Sorensen-Dice dissimilarities for each pair of factors or for the index.",
      "topics": [
        "csorensendice"
      ]
    },
    {
      "page": "generate_report_cbhattacharyya",
      "title": "Generate a Microsoft Word document about the Bhattacharyya dissimilarities matrix or matrices (two or more) and the p-values matrix or matrices (two or more).",
      "topics": [
        "generate_report_cbhattacharyya"
      ]
    },
    {
      "page": "generate_report_cbraycurtis",
      "title": "Generate a Microsoft Word document about the Bray-Curtis dissimilarities matrix or matrices (two or more) and the p-values matrix or matrices (two or more).",
      "topics": [
        "generate_report_cbraycurtis"
      ]
    },
    {
      "page": "generate_report_ccanberra",
      "title": "Generate a Microsoft Word document about the Canberra distances matrix or matrices (two or more) and the p-values matrix or matrices (two or more).",
      "topics": [
        "generate_report_ccanberra"
      ]
    },
    {
      "page": "generate_report_cchebyshev",
      "title": "Generate a Microsoft Word document about the Chebyshev distances matrix or matrices (two or more) and the p-values matrix or matrices (two or more).",
      "topics": [
        "generate_report_cchebyshev"
      ]
    },
    {
      "page": "generate_report_ccosine",
      "title": "Generate a Microsoft Word document about the Cosine dissimilarities matrix or matrices (two or more) and the p-values matrix or matrices (two or more).",
      "topics": [
        "generate_report_ccosine"
      ]
    },
    {
      "page": "generate_report_ceuclide",
      "title": "Generate a Microsoft Word document about the Euclidean distances matrix or matrices and the p-values matrix or matrices.",
      "topics": [
        "generate_report_ceuclide"
      ]
    },
    {
      "page": "generate_report_chamming",
      "title": "Generate a Microsoft Word document about the Hamming distances matrix or matrices (two or more) and the p-values matrix or matrices (two or more).",
      "topics": [
        "generate_report_chamming"
      ]
    },
    {
      "page": "generate_report_chellinger",
      "title": "Generate a Microsoft Word document about the Hellinger distances matrix or matrices (two or more) and the p-values matrix or matrices (two or more).",
      "topics": [
        "generate_report_chellinger"
      ]
    },
    {
      "page": "generate_report_cjaccard",
      "title": "Generate a Microsoft Word document about the Jaccard distances matrix or matrices (two or more) and the p-values matrix or matrices (two or more).",
      "topics": [
        "generate_report_cjaccard"
      ]
    },
    {
      "page": "generate_report_cmahalanobis",
      "title": "Generate a Microsoft Word document about the Mahalanobis distances matrix or matrices and the p-values matrix or matrices.",
      "topics": [
        "generate_report_cmahalanobis"
      ]
    },
    {
      "page": "generate_report_cmanhattan",
      "title": "Generate a Microsoft Word document about the Manhattan distances matrix or matrices (two or more) and the p-values matrix or matrices (two or more).",
      "topics": [
        "generate_report_cmanhattan"
      ]
    },
    {
      "page": "generate_report_cminkowski",
      "title": "Generate a Microsoft Word document about the Minkowski dissimilarities/distances matrix or matrices (two or more) and the p-values matrix or matrices (two or more).",
      "topics": [
        "generate_report_cminkowski"
      ]
    },
    {
      "page": "generate_report_csorensendice",
      "title": "Generate a Microsoft Word document about the Sorensen-Dice dissimilarity matrix or matrices (two or more) and the p-values matrix or matrices (two or more).",
      "topics": [
        "generate_report_csorensendice"
      ]
    },
    {
      "page": "pvaluescbatt",
      "title": "Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Bhattacharyya dissimilarities as a base.",
      "topics": [
        "pvaluescbatt"
      ]
    },
    {
      "page": "pvaluescbrcu",
      "title": "Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Bray-Curtis dissimilarity as a base.",
      "topics": [
        "pvaluescbrcu"
      ]
    },
    {
      "page": "pvaluesccanb",
      "title": "Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Canberra distance as a base.",
      "topics": [
        "pvaluesccanb"
      ]
    },
    {
      "page": "pvaluesccheb",
      "title": "Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Chebyshev distance as a base.",
      "topics": [
        "pvaluesccheb"
      ]
    },
    {
      "page": "pvaluesccosi",
      "title": "Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Cosine dissimilarity as a base.",
      "topics": [
        "pvaluesccosi"
      ]
    },
    {
      "page": "pvaluesceucl",
      "title": "Calculate the p_values matrix or matrices (two or more) for each pair of factors inside variable or variables (two or more), using Euclidean distance as a base.",
      "topics": [
        "pvaluesceucl"
      ]
    },
    {
      "page": "pvalueschamm",
      "title": "Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Hamming distance as a base.",
      "topics": [
        "pvalueschamm"
      ]
    },
    {
      "page": "pvalueschell",
      "title": "Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Hellinger distances as a base.",
      "topics": [
        "pvalueschell"
      ]
    },
    {
      "page": "pvaluescjacc",
      "title": "Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Jaccard distance as a base.",
      "topics": [
        "pvaluescjacc"
      ]
    },
    {
      "page": "pvaluescmaha",
      "title": "Calculate the p_values matrix or matrices (two or more) for each pair of factors inside variable or variables (two or more), using Mahalanobis distance as a base.",
      "topics": [
        "pvaluescmaha"
      ]
    },
    {
      "page": "pvaluescmanh",
      "title": "Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Manhattan distance as a base.",
      "topics": [
        "pvaluescmanh"
      ]
    },
    {
      "page": "pvaluescmink",
      "title": "Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Minkowski dissimilarity/distance as a base.",
      "topics": [
        "pvaluescmink"
      ]
    },
    {
      "page": "pvaluescsore",
      "title": "Calculate the p_values matrix or matrices (two or more) for each factor inside variable or variables (two or more), using Sorensen-Dice dissimilarity as a base.",
      "topics": [
        "pvaluescsore"
      ]
    }
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}