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. Du, Jiangze; Lai, Kin Keung: Copula-based risk management models for multivariable RMB exchange rate in the process of RMB internationalization (2017)
  2. Erdely, Arturo: A subcopula based dependence measure. (2017)
  3. Gijbels, Irène; Omelka, Marek; Pešta, Michal; Veraverbeke, Noël: Score tests for covariate effects in conditional copulas (2017)
  4. Górecki, Jan; Hofert, Marius; Holeňa, Martin: On structure, family and parameter estimation of hierarchical Archimedean copulas (2017)
  5. Janssen, Paul; Swanepoel, Jan; Veraverbeke, Noël: Smooth copula-based estimation of the conditional density function with a single covariate (2017)
  6. Kojadinovic, Ivan: Some copula inference procedures adapted to the presence of ties (2017)
  7. Komorník, Jozef; Komorníková, Magda; Kalická, Jana: Dependence measures for perturbations of copulas (2017)
  8. Marra, Giampiero; Radice, Rosalba: Bivariate copula additive models for location, scale and shape (2017)
  9. Pircalabelu, Eugen; Claeskens, Gerda; Gijbels, Irène: Copula directed acyclic graphs (2017)
  10. Rodríguez-Picón, Luis Alberto; Flores-Ochoa, Víctor Hugo; Méndez-González, Luis Carlos; Rodríguez-Medina, Manuel Arnoldo: Bivariate degradation modelling with marginal heterogeneous stochastic processes (2017)
  11. Segers, Johan; Sibuya, Masaaki; Tsukahara, Hideatsu: The empirical beta copula (2017)
  12. Shi, Xiaojun; Tang, Qihe; Yuan, Zhongyi: A limit distribution of credit portfolio losses with low default probabilities (2017)
  13. Sukparungsee, Saowanit; Kuvattana, Sasigarn; Busababodhin, Piyapatr; Areepong, Yupaporn: Multivariate copulas on the MCUSUM control chart (2017)
  14. Tran, Hien Duy; Pham, Uyen Hoang; Ly, Sel; Vo-Duy, T.: Extraction dependence structure of distorted copulas via a measure of dependence (2017)
  15. Bücher, Axel; Kojadinovic, Ivan: An overview of nonparametric tests of extreme-value dependence and of some related statistical procedures (2016)
  16. Di Lascio, F. Marta L.; Durante, Fabrizio; Jaworski, Piotr: Truncation invariant copulas and a testing procedure (2016)
  17. Huser, Raphaël; Davison, Anthony C.; Genton, Marc G.: Likelihood estimators for multivariate extremes (2016)
  18. Kojadinovic, Ivan; Quessy, Jean-François; Rohmer, Tom: Testing the constancy of Spearman’s rho in multivariate time series (2016)
  19. Kosmidis, Ioannis; Karlis, Dimitris: Model-based clustering using copulas with applications (2016)
  20. Matsypura, Dmytro; Neo, Emily; Prokhorov, Artem: Estimation of hierarchical Archimedean copulas as a shortest path problem (2016)