cort: 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) <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.

Version:	0.3.1
Depends:	R (≥ 2.10)
Imports:	Rdpack, methods, purrr, nloptr, osqp, Rcpp, furrr
LinkingTo:	Rcpp
Suggests:	covr, testthat (≥ 2.1.0), spelling, knitr, rmarkdown
Published:	2020-05-13
Author:	Oskar Laverny [aut, cre]
Maintainer:	Oskar Laverny <oskar.laverny at gmail.com>
BugReports:	https://github.com/lrnv/cort/issues
License:	MIT + file LICENSE
URL:	https://github.com/lrnv/cort
NeedsCompilation:	yes
Language:	en-US
Materials:	README NEWS
CRAN checks:	cort results

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