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) <doi:10.1080/03610926.2019.1586936> 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) <arXiv:2005.02912>, 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.
|Depends:||R (≥ 2.10)|
|Imports:||Rdpack, methods, purrr, nloptr, osqp, Rcpp, furrr (≥ 0.2.0)|
|Suggests:||covr, testthat (≥ 2.1.0), spelling, knitr, rmarkdown|
|Author:||Oskar Laverny [aut, cre]|
|Maintainer:||Oskar Laverny <oskar.laverny at gmail.com>|
|License:||MIT + file LICENSE|
|CRAN checks:||cort results|
1. Empirical Checkerboard Copula
2. The Copula Recursive Tree
3. Empirical Checkerboard Copula with known margins
4. Convex mixture of m-randomized checkerboards
|Windows binaries:||r-devel: cort_0.3.2.zip, r-release: cort_0.3.2.zip, r-oldrel: cort_0.3.2.zip|
|macOS binaries:||r-release (arm64): cort_0.3.2.tgz, r-release (x86_64): cort_0.3.2.tgz, r-oldrel: cort_0.3.2.tgz|
|Old sources:||cort archive|
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