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 93 articles , 1 standard article )

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  1. Allevi, E.; Boffino, L.; De Giuli, M. E.; Oggioni, G.: Analysis of long-term natural gas contracts with vine copulas in optimization portfolio problems (2019)
  2. Bücher, Axel; Fermanian, Jean-David; Kojadinovic, Ivan: Combining cumulative sum change-point detection tests for assessing the stationarity of univariate time series (2019)
  3. Arbenz, Philipp; Cambou, Mathieu; Hofert, Marius; Lemieux, Christiane; Taniguchi, Yoshihiro: Importance sampling and stratification for copula models (2018)
  4. Berghaus, Betina; Segers, Johan: Weak convergence of the weighted empirical beta copula process (2018)
  5. Eckert, Johanna; Gatzert, Nadine: Risk- and value-based management for non-life insurers under solvency constraints (2018)
  6. Einmahl, John H. J.; Kiriliouk, Anna; Segers, Johan: A continuous updating weighted least squares estimator of tail dependence in high dimensions (2018)
  7. Fasiolo, Matteo; Wood, Simon N.; Hartig, Florian; Bravington, Mark V.: An extended empirical saddlepoint approximation for intractable likelihoods (2018)
  8. Guillou, Armelle; Padoan, Simone A.; Rizzelli, Stefano: Inference for asymptotically independent samples of extremes (2018)
  9. Hofert, Marius; Huser, Raphaël; Prasad, Avinash: Hierarchical Archimax copulas (2018)
  10. Kiriliouk, Anna; Segers, Johan; Tafakori, Laleh: An estimator of the stable tail dependence function based on the empirical beta copula (2018)
  11. Marozzi, Marco: Tests for comparison of multiple endpoints with application to omics data (2018)
  12. Punzo, Antonio; Bagnato, Luca; Maruotti, Antonello: Compound unimodal distributions for insurance losses (2018)
  13. Stübinger, Johannes; Mangold, Benedikt; Krauss, Christopher: Statistical arbitrage with vine copulas (2018)
  14. Sukparungsee, Saowanit; Kuvattana, Sasigarn; Busababodhin, Piyapatr; Areepong, Yupaporn: Bivariate copulas on the Hotelling’s (T^2) control chart (2018)
  15. Tajvidi, N.; Turlach, B. A.: A general approach to generate random variates for multivariate copulae (2018)
  16. Vettori, Sabrina; Huser, Raphaël; Genton, Marc G.: A comparison of dependence function estimators in multivariate extremes (2018)
  17. Bilodeau, Martin; Nangue, Aurélien Guetsop: Tests of mutual or serial independence of random vectors with applications (2017)
  18. Bücher, Axel; Kinsvater, Paul; Kojadinovic, Ivan: Detecting breaks in the dependence of multivariate extreme-value distributions (2017)
  19. Du, Jiangze; Lai, Kin Keung: Copula-based risk management models for multivariable RMB exchange rate in the process of RMB internationalization (2017)
  20. Erdely, Arturo: A subcopula based dependence measure. (2017)

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