Some Empiric and Nonparametric Copula Models

Provides S4 classes and methods to fit several copula models: The classic empirical checkerboard copula and the empirical checkerboard copula with known margins, see Cuberos, Masiello and Maume-Deschamps (2019) are proposed. These two models allow to fit copulas in high dimension with a small number of observations, and they are always proper copulas. Some flexibility is added via a possibility to differentiate the checkerboard parameter by dimension. The last model consist of the implementation of the Copula Recursive Tree algorithm proposed by Laverny, Maume-Deschamps, Masiello and Rullière (2020) , including the localised dimension reduction, which fits a copula by recursive splitting of the copula domain. We also provide an efficient way of mixing copulas, allowing to bag the algorithm into a forest, and a generic way of measuring d-dimensional boxes with a copula.


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0.3.2 by Oskar Laverny, a year ago

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Authors: Oskar Laverny [aut, cre]

Documentation:   PDF Manual  

Task views: Probability Distributions

MIT + file LICENSE license

Imports Rdpack, methods, purrr, nloptr, osqp, Rcpp, furrr

Suggests covr, testthat, spelling, knitr, rmarkdown

Linking to Rcpp

See at CRAN