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 139 articles , 1 standard article )

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  1. Elberg, Christina; Hagspiel, Simeon: Spatial dependencies of wind power and interrelations with spot price dynamics (2015)
  2. Foldnes, Njål; Grønneberg, Steffen: How general is the Vale-Maurelli simulation approach? (2015)
  3. Gijbels, Irène; Omelka, Marek; Veraverbeke, Noël: Partial and average copulas and association measures (2015)
  4. He, H.; Wang, W.; Hu, J.; Gallop, R.; Crits-Christoph, P.; Xia, Y.: Distribution-free inference of zero-inflated binomial data for longitudinal studies (2015)
  5. Hlubinka, Daniel; Šiman, Miroslav: On generalized elliptical quantiles in the nonlinear quantile regression setup (2015)
  6. Lau, John W.; Cripps, Edward: Stick-breaking representation and computation for normalized generalized gamma processes (2015)
  7. Targino, Rodrigo S.; Peters, Gareth W.; Shevchenko, Pavel V.: Sequential Monte Carlo samplers for capital allocation under copula-dependent risk models (2015)
  8. Yu, Wenbao; Park, Taesung: Two simple algorithms on linear combination of multiple biomarkers to maximize partial area under the ROC curve (2015)
  9. Bücher, Axel; Kojadinovic, Ivan; Rohmer, Tom; Segers, Johan: Detecting changes in cross-sectional dependence in multivariate time series (2014)
  10. Charest, Lysiane; Plante, Jean-François: Using balanced iterative reducing and clustering hierarchies to compute approximate rank statistics on massive datasets (2014)
  11. Geir Berentsen; Tore Kleppe; Dag Tjøstheim: Introducing localgauss, an R Package for Estimating and Visualizing Local Gaussian Correlation (2014) not zbMATH
  12. Jakob, Kevin; Fischer, Matthias: Quantifying the impact of different copulas in a generalized CreditRisk(^+) framework. An empirical study (2014)
  13. Jäschke, Stefan: Estimation of risk measures in energy portfolios using modern copula techniques (2014)
  14. Jordanger, Lars Arne; Tjøstheim, Dag: Model selection of copulas: AIC versus a cross validation copula information criterion (2014)
  15. Kauermann, Göran; Meyer, Renate: Penalized marginal likelihood estimation of finite mixtures of Archimedean copulas (2014)
  16. Kim, Daeyoung; Kim, Jong-Min: Analysis of directional dependence using asymmetric copula-based regression models (2014)
  17. Marozzi, Marco: Testing for concordance between several criteria (2014)
  18. Nooraee, Nazanin; Molenberghs, Geert; van den Heuvel, Edwin R.: GEE for longitudinal ordinal data: comparing R-geepack, R-multgee, R-repolr, SAS-GENMOD, SPSS-GENLIN (2014)
  19. Salinas-Gutiérrez, Rogelio; Hernández-Aguirre, Arturo; Villa-Diharce, Enrique R.: Copula selection for graphical models in continuous estimation of distribution algorithms (2014)
  20. Schomaker, Michael; Heumann, Christian: Model selection and model averaging after multiple imputation (2014)