CondCopulas: Estimation and Inference for Conditional Copula Models

Provides functions for the estimation of conditional copulas models, various estimators of conditional Kendall's tau (proposed in Derumigny and Fermanian (2019a, 2019b, 2020) <doi:10.1515/demo-2019-0016>, <doi:10.1016/j.csda.2019.01.013>, <doi:10.1016/j.jmva.2020.104610>), and test procedures for the simplifying assumption (proposed in Derumigny and Fermanian (2017) <doi:10.1515/demo-2017-0011> and Derumigny, Fermanian and Min (2020) <arXiv:2008.09498>).

Version: 0.1.1
Imports: VineCopula, pbapply, glmnet, ordinalNet, tree, nnet, data.tree, statmod, pcaPP
Suggests: MASS, knitr, rmarkdown, ggplot2, mvtnorm
Published: 2022-03-30
Author: Alexis Derumigny ORCID iD [aut, cre], Jean-David Fermanian ORCID iD [ctb, ths], Aleksey Min ORCID iD [ctb], Rutger van der Spek [ctb]
Maintainer: Alexis Derumigny <a.f.f.derumigny at tudelft.nl>
BugReports: https://github.com/AlexisDerumigny/CondCopulas/issues
License: GPL-3
URL: https://github.com/AlexisDerumigny/CondCopulas
NeedsCompilation: no
Materials: README NEWS
CRAN checks: CondCopulas results

Documentation:

Reference manual: CondCopulas.pdf
Vignettes: Simulation and estimation from conditional copula models

Downloads:

Package source: CondCopulas_0.1.1.tar.gz
Windows binaries: r-devel: CondCopulas_0.1.1.zip, r-release: CondCopulas_0.1.1.zip, r-oldrel: CondCopulas_0.1.1.zip
macOS binaries: r-release (arm64): CondCopulas_0.1.1.tgz, r-release (x86_64): CondCopulas_0.1.1.tgz, r-oldrel: CondCopulas_0.1.1.tgz

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