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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 1.0.0). 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",
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  "SystemRequirements": "C++17",
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  "BugReports": "https://github.com/vinecopulib/rvinecopulib/issues",
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  "Author": "Thomas Nagler [aut, cre],\nThibault Vatter [aut]",
  "Maintainer": "Thomas Nagler <info@vinecopulib.org>",
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  "_exports": [
    "as_margin",
    "as_rvine_matrix",
    "as_rvine_structure",
    "as.bicop",
    "bicop",
    "bicop_dist",
    "blomqvist_beta",
    "cvine_structure",
    "dbicop",
    "dmargin",
    "dvine",
    "dvine_structure",
    "dvinecop",
    "emp_cdf",
    "fit_margin",
    "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",
    "hessian",
    "inverse_rosenblatt",
    "is.rvine_matrix",
    "is.rvine_structure",
    "kde1d_family",
    "ktau_to_par",
    "margin_dist",
    "margin_family",
    "margin_info",
    "mBICV",
    "pairs_copula_data",
    "par_to_ktau",
    "pbicop",
    "pmargin",
    "pseudo_obs",
    "pvine",
    "pvinecop",
    "qmargin",
    "rbicop",
    "rosenblatt",
    "rvine",
    "rvine_matrix",
    "rvine_matrix_sim",
    "rvine_structure",
    "rvine_structure_sim",
    "rvinecop",
    "scores",
    "stats_margin",
    "tail_dep",
    "truncate_model",
    "univariateML_family",
    "vine",
    "vine_dist",
    "vinecop",
    "vinecop_dist",
    "zero_inflated"
  ],
  "_help": [
    {
      "page": "as_margin",
      "title": "Normalize an object to the fitted-margin protocol",
      "topics": [
        "as_margin"
      ]
    },
    {
      "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_dependence",
      "title": "Dependence measures of a bivariate copula",
      "topics": [
        "bicop_dependence",
        "blomqvist_beta",
        "tail_dep"
      ]
    },
    {
      "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",
        "hessian.bicop_dist",
        "pbicop",
        "pbicop_dist",
        "rbicop",
        "rbicop_dist",
        "scores.bicop_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": "kde1d_family",
      "title": "Define a kde1d margin family",
      "topics": [
        "kde1d_family"
      ]
    },
    {
      "page": "margin_dist",
      "title": "Create a fitted or fixed custom margin",
      "topics": [
        "margin_dist"
      ]
    },
    {
      "page": "margin_family",
      "title": "Define a custom margin family",
      "topics": [
        "margin_family"
      ]
    },
    {
      "page": "margin_family_protocol",
      "title": "Margin-family fitting protocol",
      "topics": [
        "fit_margin",
        "margin_family_protocol"
      ]
    },
    {
      "page": "margin_protocol",
      "title": "Fitted marginal distribution protocol",
      "topics": [
        "dmargin",
        "margin_info",
        "margin_protocol",
        "pmargin",
        "qmargin"
      ]
    },
    {
      "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": "parameter_uncertainty",
      "title": "Parameter uncertainty",
      "topics": [
        "confint.bicop_dist",
        "confint.vinecop_dist",
        "parameter_uncertainty",
        "vcov.bicop_dist",
        "vcov.vinecop_dist"
      ]
    },
    {
      "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": "Rosenblatt and inverse Rosenblatt transforms",
      "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": "stats_margin",
      "title": "Create a fixed margin from a stats distribution",
      "topics": [
        "stats_margin"
      ]
    },
    {
      "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": "univariateML_family",
      "title": "Define a univariateML margin family",
      "topics": [
        "univariateML_family"
      ]
    },
    {
      "page": "vine",
      "title": "Vine copula models",
      "topics": [
        "vine",
        "vine_dist"
      ]
    },
    {
      "page": "vine_methods",
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