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.
Package details |
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Author | Oskar Laverny [aut, cre] (<https://orcid.org/0000-0002-7508-999X>) |
Maintainer | Oskar Laverny <oskar.laverny@gmail.com> |
License | MIT + file LICENSE |
Version | 0.3.2 |
URL | https://github.com/lrnv/cort |
Package repository | View on CRAN |
Installation |
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