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  "Title": "Ordinal Time Series Analysis",
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  "Authors@R": "c(\nperson(\"Angel\", \"Lopez-Oriona\", email = \"oriona38@hotmail.com\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Jose\", \"A. Vilar\", role = \"aut\"))",
  "Description": "An implementation of several functions for feature\nextraction in ordinal time series datasets. Specifically, some\nof the features proposed by Weiss (2019)\n<doi:10.1080/01621459.2019.1604370> can be computed. These\nfeatures can be used to perform inferential tasks or to feed\nmachine learning algorithms for ordinal time series, among\nothers. The package also includes some interesting datasets\ncontaining financial time series. Practitioners from a broad\nvariety of fields could benefit from the general framework\nprovided by 'otsfeatures'.",
  "License": "GPL-2",
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    "Date": "2026-05-25 10:03:59 UTC",
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  "Author": "Angel Lopez-Oriona [aut, cre], Jose A. Vilar [aut]",
  "Maintainer": "Angel Lopez-Oriona <oriona38@hotmail.com>",
  "Repository": "https://anloor7.r-universe.dev",
  "Date/Publication": "2023-03-01 09:40:02 UTC",
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    "c_joint_probabilities",
    "c_marginal_probabilities",
    "ci_ordinal_asymmetry",
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    "joint_probabilities",
    "marginal_probabilities",
    "ordinal_asymmetry",
    "ordinal_cohens_kappa",
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    "ordinal_dispersion_2",
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    "ordinal_location_2",
    "ordinal_skewness",
    "ots_plot",
    "plot_ordinal_cohens_kappa",
    "test_ordinal_asymmetry",
    "test_ordinal_dispersion",
    "test_ordinal_skewness",
    "total_c_correlation",
    "total_mixed_c_correlation_1",
    "total_mixed_c_correlation_2"
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      "title": "AustrianWages",
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      "table": true,
      "tojson": true
    },
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      "title": "CreditRatings",
      "object": "CreditRatings",
      "class": [
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      ],
      "fields": [],
      "table": true,
      "tojson": true
    },
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      "title": "SyntheticData1",
      "object": "SyntheticData1",
      "class": [
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      ],
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      "table": true,
      "tojson": true
    },
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      "title": "SyntheticData2",
      "object": "SyntheticData2",
      "class": [
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      ],
      "fields": [],
      "table": true,
      "tojson": true
    },
    {
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      "title": "SyntheticData3",
      "object": "SyntheticData3",
      "class": [
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      ],
      "fields": [],
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "AustrianWages",
      "title": "AustrianWages",
      "topics": [
        "AustrianWages"
      ]
    },
    {
      "page": "binarization",
      "title": "Constructs the binarized time series associated with a given ordinal time series",
      "topics": [
        "binarization"
      ]
    },
    {
      "page": "c_binarization",
      "title": "Constructs the cumulative binarized time series associated with a given ordinal time series",
      "topics": [
        "c_binarization"
      ]
    },
    {
      "page": "c_conditional_probabilities",
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      "topics": [
        "c_conditional_probabilities"
      ]
    },
    {
      "page": "c_joint_probabilities",
      "title": "Computes the cumulative joint probabilities of an ordinal time series",
      "topics": [
        "c_joint_probabilities"
      ]
    },
    {
      "page": "c_marginal_probabilities",
      "title": "Computes the cumulative marginal probabilities of an ordinal time series",
      "topics": [
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      ]
    },
    {
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      ]
    },
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      "topics": [
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      ]
    },
    {
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      ]
    },
    {
      "page": "conditional_probabilities",
      "title": "Computes the conditional probabilities of an ordinal time series",
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      ]
    },
    {
      "page": "CreditRatings",
      "title": "CreditRatings",
      "topics": [
        "CreditRatings"
      ]
    },
    {
      "page": "index_ordinal_variation",
      "title": "Computes the estimated index of ordinal variation (IOV) of an ordinal time series",
      "topics": [
        "index_ordinal_variation"
      ]
    },
    {
      "page": "joint_probabilities",
      "title": "Computes the joint probabilities of an ordinal time series",
      "topics": [
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      ]
    },
    {
      "page": "marginal_probabilities",
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      "topics": [
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      ]
    },
    {
      "page": "ordinal_asymmetry",
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      ]
    },
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      "topics": [
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      ]
    },
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      "page": "ordinal_dispersion_1",
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      "topics": [
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      ]
    },
    {
      "page": "ordinal_dispersion_2",
      "title": "Computes the estimated dispersion of an ordinal time series according to the approach based on the diversity coefficient (DIVC)",
      "topics": [
        "ordinal_dispersion_2"
      ]
    },
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      ]
    },
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      "title": "Computes the estimated location of an ordinal time series with respect to the lowest category",
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      ]
    },
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    },
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      "page": "ots_plot",
      "title": "Constructs an ordinal time series plot",
      "topics": [
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      ]
    },
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      "topics": [
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