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  "Title": "High Performance Algorithms for Vine Copula Modeling",
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  "Description": "Provides an interface to 'vinecopulib', a C++ library for\nvine copula modeling. The 'rvinecopulib' package implements the\ncore features of the popular 'VineCopula' package, in\nparticular inference algorithms for both vine copula and\nbivariate copula models. Advantages over 'VineCopula' are a\nsleeker and more modern API, improved performances, especially\nin high dimensions, nonparametric and multi-parameter families,\nand the ability to model discrete variables. The 'rvinecopulib'\npackage includes 'vinecopulib' as header-only C++ library\n(currently version 0.7.2). Thus users do not need to install\n'vinecopulib' itself in order to use 'rvinecopulib'. Since\ntheir initial releases, 'vinecopulib' is licensed under the MIT\nLicense, and 'rvinecopulib' is licensed under the GNU GPL\nversion 3.",
  "License": "GPL-3 | file LICENSE",
  "Encoding": "UTF-8",
  "NeedsCompilation": "yes",
  "BugReports": "https://github.com/vinecopulib/rvinecopulib/issues",
  "URL": "https://vinecopulib.github.io/rvinecopulib/",
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  "Date/Publication": "2025-06-13 13:04:03 UTC",
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  "Packaged": {
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  "Author": "Thomas Nagler [aut, cre],\nThibault Vatter [aut]",
  "Maintainer": "Thomas Nagler <info@vinecopulib.org>",
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    "message": "Release 0.7.3.1.0 (#312)\n\n* Random spanning tree (#307)\n\n* random spanning tree\n\n* add unit test\n\n* mst_algorithm to tree_algorithm\n\n* formatting\n\n* remove file\n\n* more entropy and randomize wilson's root\n\n* don't forget vine.R\n\n* document\n\n* pull latest vinecopulib\n\n* remove pragma suppressing diagnostics\n\n* automatize tools_integration directives removal\n\n* automatize tools_integration directives removal+1\n\n* Use air as formatter (#310)\n\n* Switch to air\n\n* Run air format .\n\n* Add GitHub action\n\n* Prepare release v0.7.3 (#311)\n\n* Switch to air\n\n* Run air format .\n\n* Add GitHub action\n\n* Pull vinecopulib v0.7.3\n\n* Update news and description\n\n* Remove old version header\n\n* update website",
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    "as_rvine_structure",
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    "bicop",
    "bicop_dist",
    "cvine_structure",
    "dbicop",
    "dvine",
    "dvine_structure",
    "dvinecop",
    "emp_cdf",
    "get_all_families",
    "get_all_ktaus",
    "get_all_pair_copulas",
    "get_all_parameters",
    "get_family",
    "get_ktau",
    "get_matrix",
    "get_pair_copula",
    "get_parameters",
    "get_structure",
    "hbicop",
    "inverse_rosenblatt",
    "is.rvine_matrix",
    "is.rvine_structure",
    "ktau_to_par",
    "mBICV",
    "pairs_copula_data",
    "par_to_ktau",
    "pbicop",
    "pseudo_obs",
    "pvine",
    "pvinecop",
    "rbicop",
    "rosenblatt",
    "rvine",
    "rvine_matrix",
    "rvine_matrix_sim",
    "rvine_structure",
    "rvine_structure_sim",
    "rvinecop",
    "truncate_model",
    "vine",
    "vine_dist",
    "vinecop",
    "vinecop_dist"
  ],
  "_help": [
    {
      "page": "as_rvine_structure",
      "title": "Coerce various kind of objects to R-vine structures and matrices",
      "topics": [
        "as_rvine_matrix",
        "as_rvine_matrix.list",
        "as_rvine_matrix.matrix",
        "as_rvine_matrix.rvine_matrix",
        "as_rvine_matrix.rvine_structure",
        "as_rvine_structure",
        "as_rvine_structure.list",
        "as_rvine_structure.matrix",
        "as_rvine_structure.rvine_matrix",
        "as_rvine_structure.rvine_structure"
      ]
    },
    {
      "page": "as.bicop",
      "title": "Convert list to bicop object",
      "topics": [
        "as.bicop"
      ]
    },
    {
      "page": "bicop",
      "title": "Fit and select bivariate copula models",
      "topics": [
        "bicop"
      ]
    },
    {
      "page": "bicop_dist",
      "title": "Bivariate copula models",
      "topics": [
        "bicop_dist"
      ]
    },
    {
      "page": "bicop_methods",
      "title": "Bivariate copula distributions",
      "topics": [
        "bicop_distributions",
        "dbicop",
        "dbicop_dist",
        "hbicop",
        "hbicop_dist",
        "pbicop",
        "pbicop_dist",
        "rbicop",
        "rbicop_dist"
      ]
    },
    {
      "page": "predict_bicop",
      "title": "Predictions and fitted values for a bivariate copula model",
      "topics": [
        "bicop_predict_and_fitted",
        "fitted.bicop",
        "predict.bicop",
        "predict.bicop_dist"
      ]
    },
    {
      "page": "emp_cdf",
      "title": "Corrected Empirical CDF",
      "topics": [
        "emp_cdf"
      ]
    },
    {
      "page": "getters",
      "title": "Extracts components of 'bicop_dist' and 'vinecop_dist' objects",
      "topics": [
        "getters",
        "get_all_families",
        "get_all_ktaus",
        "get_all_pair_copulas",
        "get_all_parameters",
        "get_family",
        "get_ktau",
        "get_matrix",
        "get_pair_copula",
        "get_parameters",
        "get_structure"
      ]
    },
    {
      "page": "mBICV",
      "title": "Modified vine copula Bayesian information criterion (mBICv)",
      "topics": [
        "mBICV"
      ]
    },
    {
      "page": "pairs_copula_data",
      "title": "Exploratory pairs plot for copula data",
      "topics": [
        "pairs_copula_data"
      ]
    },
    {
      "page": "par_to_ktau",
      "title": "Conversion between Kendall's tau and parameters",
      "topics": [
        "ktau_to_par",
        "par_to_ktau"
      ]
    },
    {
      "page": "plot.bicop_dist",
      "title": "Plotting tools for 'bicop_dist' and 'bicop' objects",
      "topics": [
        "contour.bicop",
        "contour.bicop_dist",
        "plot.bicop",
        "plot.bicop_dist"
      ]
    },
    {
      "page": "plot.rvine_structure",
      "title": "Plotting R-vine structures",
      "topics": [
        "plot.rvine_matrix",
        "plot.rvine_structure"
      ]
    },
    {
      "page": "plot.vinecop_dist",
      "title": "Plotting 'vinecop_dist' and 'vinecop' objects.",
      "topics": [
        "contour.vinecop",
        "contour.vinecop_dist",
        "plot.vinecop",
        "plot.vinecop_dist"
      ]
    },
    {
      "page": "pseudo_obs",
      "title": "Pseudo-Observations",
      "topics": [
        "pseudo_obs"
      ]
    },
    {
      "page": "rosenblatt",
      "title": "(Inverse) Rosenblatt transform",
      "topics": [
        "inverse_rosenblatt",
        "rosenblatt"
      ]
    },
    {
      "page": "rvine_structure",
      "title": "R-vine structure",
      "topics": [
        "cvine_structure",
        "dvine_structure",
        "is.rvine_matrix",
        "is.rvine_structure",
        "rvine_matrix",
        "rvine_structure"
      ]
    },
    {
      "page": "rvine_structure_sim",
      "title": "Simulate R-vine structures",
      "topics": [
        "rvine_matrix_sim",
        "rvine_structure_sim"
      ]
    },
    {
      "page": "rvinecopulib",
      "title": "High Performance Algorithms for Vine Copula Modeling",
      "topics": [
        "rvinecopulib-package",
        "rvinecopulib"
      ]
    },
    {
      "page": "truncate_model",
      "title": "Truncate a vine copula model",
      "topics": [
        "truncate_model",
        "truncate_model.rvine_matrix",
        "truncate_model.rvine_structure",
        "truncate_model.vinecop_dist",
        "truncate_model.vine_dist"
      ]
    },
    {
      "page": "vine",
      "title": "Vine copula models",
      "topics": [
        "vine",
        "vine_dist"
      ]
    },
    {
      "page": "vine_methods",
      "title": "Vine based distributions",
      "topics": [
        "dvine",
        "dvine_dist",
        "pvine",
        "pvine_dist",
        "rvine",
        "rvine_dist",
        "vine_distributions"
      ]
    },
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        "predict.vine",
        "vine_predict_and_fitted"
      ]
    },
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      "page": "vinecop",
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      ]
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      "title": "Vine copula models",
      "topics": [
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      "title": "Vine copula distributions",
      "topics": [
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        "pvinecop",
        "pvinecop_dist",
        "rvinecop",
        "rvinecop_dist",
        "vinecop_distributions"
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      "title": "Predictions and fitted values for a vine copula model",
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        "predict.vinecop",
        "vinecop_predict_and_fitted"
      ]
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