copula

Enjoy the Joy of Copulas: With a Package copula. Copulas have become a popular tool in multivariate modeling successfully applied in many fields. A good open-source implementation of copulas is much needed for more practitioners to enjoy the joy of copulas. This article presents the design, features, and some implementation details of the R package copula. The package provides a carefully designed and easily extensible platform for multivariate modeling with copulas in R. S4 classes for most frequently used elliptical copulas and Archimedean copulas are implemented, with methods for density/distribution evaluation, random number generation, and graphical display. Fitting copula-based models with maximum likelihood method is provided as template examples. With the classes and methods in the package, the package can be easily extended by user-defined copulas and margins to solve problems

This software is also peer reviewed by journal JSS.


References in zbMATH (referenced in 147 articles , 1 standard article )

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  1. Eckert, Johanna; Gatzert, Nadine: Risk- and value-based management for non-life insurers under solvency constraints (2018)
  2. Einmahl, John H. J.; Kiriliouk, Anna; Segers, Johan: A continuous updating weighted least squares estimator of tail dependence in high dimensions (2018)
  3. Fasiolo, Matteo; Wood, Simon N.; Hartig, Florian; Bravington, Mark V.: An extended empirical saddlepoint approximation for intractable likelihoods (2018)
  4. Guillou, Armelle; Padoan, Simone A.; Rizzelli, Stefano: Inference for asymptotically independent samples of extremes (2018)
  5. Hofert, Marius; Huser, Raphaël; Prasad, Avinash: Hierarchical Archimax copulas (2018)
  6. Hofert, Marius; Kojadinovic, Ivan; Mächler, Martin; Yan, Jun: Elements of copula modeling with R (2018)
  7. Kiriliouk, Anna; Segers, Johan; Tafakori, Laleh: An estimator of the stable tail dependence function based on the empirical beta copula (2018)
  8. Li, Dingfang; Gui, Yifan; Li, Yifan; Xiong, Lihua: A method for constructing asymmetric pair-copula and its application (2018)
  9. Marozzi, Marco: Tests for comparison of multiple endpoints with application to omics data (2018)
  10. Pérez-Ruiz, Luis Carlos; Escarela, Gabriel: Joint regression modeling for missing categorical covariates in generalized linear models (2018)
  11. Punzo, Antonio; Bagnato, Luca; Maruotti, Antonello: Compound unimodal distributions for insurance losses (2018)
  12. Stübinger, Johannes; Mangold, Benedikt; Krauss, Christopher: Statistical arbitrage with vine copulas (2018)
  13. Sukparungsee, Saowanit; Kuvattana, Sasigarn; Busababodhin, Piyapatr; Areepong, Yupaporn: Bivariate copulas on the Hotelling’s (T^2) control chart (2018)
  14. Tajvidi, N.; Turlach, B. A.: A general approach to generate random variates for multivariate copulae (2018)
  15. Vettori, Sabrina; Huser, Raphaël; Genton, Marc G.: A comparison of dependence function estimators in multivariate extremes (2018)
  16. Wanke, P.; Barros, C. P.; Emrouznejad, A.: A comparison between stochastic DEA and fuzzy DEA approaches: revisiting efficiency in Angolan banks (2018)
  17. Bilodeau, Martin; Nangue, Aurélien Guetsop: Tests of mutual or serial independence of random vectors with applications (2017)
  18. Bücher, Axel; Irresberger, Felix; Weiss, Gregor N. F.: Testing asymmetry in dependence with Copula-coskewness (2017)
  19. Bücher, Axel; Kinsvater, Paul; Kojadinovic, Ivan: Detecting breaks in the dependence of multivariate extreme-value distributions (2017)
  20. de Oliveira, Ricardo T. A.; de Assis, Thaíze Fernandes O.; Firmino, Paulo Renato A.; Ferreira, Tiago A. E.: Copulas-based time series combined forecasters (2017)