nacopula: Nested Archimedean Copulas. An R package for working with nested Archimedean copulas. Specifically, providing procedures for computing function values and cube volumes, characteristics such as Kendall’s tau and tail dependence coefficients, efficient sampling algorithms, various estimators, and goodness-of-fit tests. The package also contains related univariate distributions and special functions such as the Sibuya distribution, the polylogarithm, Stirling and Eulerian numbers.

References in zbMATH (referenced in 49 articles , 2 standard articles )

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  1. Alanazi, Fadhah Amer: A mixture of regular vines for multiple dependencies (2021)
  2. Deng, Yihao; Chaganty, N. R.: Pair-copula models for analyzing family data (2021)
  3. Yuan, Zhenfei; Hu, Taizhong: pyvine: the Python package for regular vine copula modeling, sampling and testing (2021)
  4. Islam, Shofiqul; Anand, Sonia; Hamid, Jemila; Thabane, Lehana; Beyene, Joseph: A copula-based method of classifying individuals into binary disease categories using dependent biomarkers (2020)
  5. Jan Górecki, Marius Hofert, Martin Holeňa: Hierarchical Archimedean Copulas for MATLAB and Octave: The HACopula Toolbox (2020) not zbMATH
  6. Li, Dongdong; Hu, X. Joan; McBride, Mary L.; Spinelli, John J.: Multiple event times in the presence of informative censoring: modeling and analysis by copulas (2020)
  7. Lo, Simon M. S.; Mammen, Enno; Wilke, Ralf A.: A nested copula duration model for competing risks with multiple spells (2020)
  8. Oskar Laverny: Empirical and non-parametric copula models with the cort R package (2020) not zbMATH
  9. Arbenz, Philipp; Cambou, Mathieu; Hofert, Marius; Lemieux, Christiane; Taniguchi, Yoshihiro: Importance sampling and stratification for copula models (2018)
  10. Cooray, Kahadawala: Strictly Archimedean copulas with complete association for multivariate dependence based on the Clayton family (2018)
  11. Cossette, Hélène; Marceau, Etienne; Mtalai, Itre; Veilleux, Déry: Dependent risk models with Archimedean copulas: a computational strategy based on common mixtures and applications (2018)
  12. Gijbels, Irène; Herrmann, Klaus: Optimal expected-shortfall portfolio selection with copula-induced dependence (2018)
  13. Gilles Durrieu, Ion Grama, Kevin Jaunatre, Quang-Khoai Pham, Jean-Marie Tricot: extremefit: A Package for Extreme Quantiles (2018) not zbMATH
  14. Hofert, Marius; Huser, Raphaël; Prasad, Avinash: Hierarchical Archimax copulas (2018)
  15. Sukparungsee, Saowanit; Kuvattana, Sasigarn; Busababodhin, Piyapatr; Areepong, Yupaporn: Bivariate copulas on the Hotelling’s (T^2) control chart (2018)
  16. Tajvidi, N.; Turlach, B. A.: A general approach to generate random variates for multivariate copulae (2018)
  17. Uyttendaele, Nathan: On the estimation of nested Archimedean copulas: a theoretical and an experimental comparison (2018)
  18. Cambou, Mathieu; Hofert, Marius; Lemieux, Christiane: Quasi-random numbers for copula models (2017)
  19. Härdle, Karl Wolfgang; Okhrin, Ostap; Okhrin, Yarema: Basic elements of computational statistics (2017)
  20. Côté, Marie-Pier; Genest, Christian; Abdallah, Anas: Rank-based methods for modeling dependence between loss triangles (2016)

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