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 145 articles , 1 standard article )

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  1. Grazian, Clara; Dalla Valle, Luciana; Liseo, Brunero: Approximate Bayesian conditional copulas (2022)
  2. Ahn, Jae Youn; Fuchs, Sebastian; Oh, Rosy: A copula transformation in multivariate mixed discrete-continuous models (2021)
  3. Alanazi, Fadhah Amer: A mixture of regular vines for multiple dependencies (2021)
  4. Berrett, Thomas B.; Kontoyiannis, Ioannis; Samworth, Richard J.: Optimal rates for independence testing via (U)-statistic permutation tests (2021)
  5. Deng, Yihao; Chaganty, N. R.: Pair-copula models for analyzing family data (2021)
  6. Farnoudkia, Hajar; Purutçuoğlu, Vilda: Vine copula graphical models in the construction of biological networks (2021)
  7. Fuchs, Sebastian; Di Lascio, F. Marta L.; Durante, Fabrizio: Dissimilarity functions for rank-invariant hierarchical clustering of continuous variables (2021)
  8. Górecki, Jan; Hofert, Marius; Okhrin, Ostap: Outer power transformations of hierarchical Archimedean copulas: construction, sampling and estimation (2021)
  9. Hallin, Marc; Mordant, Gilles; Segers, Johan: Multivariate goodness-of-fit tests based on Wasserstein distance (2021)
  10. Jaser, Miriam; Min, Aleksey: On tests for symmetry and radial symmetry of bivariate copulas towards testing for ellipticity (2021)
  11. Junker, Robert R.; Griessenberger, Florian; Trutschnig, Wolfgang: Estimating scale-invariant directed dependence of bivariate distributions (2021)
  12. Kasper, Thimo M.; Fuchs, Sebastian; Trutschnig, Wolfgang: On weak conditional convergence of bivariate Archimedean and extreme value copulas, and consequences to nonparametric estimation (2021)
  13. Kojadinovic, Ivan; Verdier, Ghislain: Nonparametric sequential change-point detection for multivariate time series based on empirical distribution functions (2021)
  14. Neumann, Matthias; Machado Charry, Eduardo; Zojer, Karin; Schmidt, Volker: On variability and interdependence of local porosity and local tortuosity in porous materials: a case study for sack paper (2021)
  15. Nowak, Claus P.; Konietschke, Frank: Simultaneous inference for Kendall’s tau (2021)
  16. Song, Zhi; Mukherjee, Amitava; Zhang, Jiujun: Some robust approaches based on copula for monitoring bivariate processes and component-wise assessment (2021)
  17. Yuan, Zhenfei; Hu, Taizhong: pyvine: the Python package for regular vine copula modeling, sampling and testing (2021)
  18. Zhang, Shulin; Zhou, Qian M.; Lin, Huazhen: Goodness-of-fit test of copula functions for semi-parametric univariate time series models (2021)
  19. Akdur, Hatice Tul Kubra; Ozonur, Deniz; Bayrak, Hulya: An adaptation of pseudo-score confidence interval method for linear mixed models (2020)
  20. Dang, Phuc Ho; Vo Thi, Truc Giang: Gaussian copula of stable random vectors and application (2020)

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