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: | 
0.1.2 | 
| Imports: | 
VineCopula, pbapply, glmnet, ordinalNet, tree, nnet, data.tree, statmod, wdm | 
| Suggests: | 
MASS, knitr, rmarkdown, ggplot2, mvtnorm | 
| Published: | 
2022-04-25 | 
| Author: | 
Alexis Derumigny  
    [aut, cre],
  Jean-David Fermanian
      [ctb, ths],
  Aleksey Min   [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 | 
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