R package CDVine: Statistical inference of C- and D-vine copulas. This package provides functions for statistical inference of canonical vine (C-vine) and D-vine copulas. It contains tools for bivariate exploratory data analysis and for bivariate as well as vine copula selection. Models can be estimated either sequentially or by joint maximum likelihood estimation. Sampling algorithms and plotting methods are also included. Data is assumed to lie in the unit hypercube (so-called copula data).

References in zbMATH (referenced in 16 articles , 1 standard article )

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  1. Pircalabelu, Eugen; Claeskens, Gerda; Gijbels, Irène: Copula directed acyclic graphs (2017)
  2. Su, Jianxi; Hua, Lei: A general approach to full-range tail dependence copulas (2017)
  3. Tekumalla, Lavanya Sita; Rajan, Vaibhav; Bhattacharyya, Chiranjib: Vine copulas for mixed data: multi-view clustering for mixed data beyond meta-Gaussian dependencies (2017)
  4. Dalla Valle, Luciana; De Giuli, Maria Elena; Tarantola, Claudia; Manelli, Claudio: Default probability estimation via pair copula constructions (2016)
  5. Kosmidis, Ioannis; Karlis, Dimitris: Model-based clustering using copulas with applications (2016)
  6. M. Wojtys; Giampiero Marra; Rosalba Radice: Copula Regression Spline Sample Selection Models: The R Package SemiParSampleSel (2016)
  7. Radice, Rosalba; Marra, Giampiero; Wojtyś, Małgorzata: Copula regression spline models for binary outcomes (2016)
  8. Cooke, R. M.; Kurowicka, D.; Wilson, Kevin J.: Sampling, conditionalizing, counting, merging, searching regular vines (2015)
  9. Erhardt, Tobias Michael; Czado, Claudia; Schepsmeier, Ulf: R-vine models for spatial time series with an application to daily mean temperature (2015)
  10. Erhardt, Tobias Michael; Czado, Claudia; Schepsmeier, Ulf: Spatial composite likelihood inference using local C-vines (2015)
  11. Gruber, Lutz; Czado, Claudia: Sequential Bayesian model selection of regular vine copulas (2015)
  12. Wiboonpongse, Aree; Liu, Jianxu; Sriboonchitta, Songsak; Denoeux, Thierry: Modeling dependence between error components of the stochastic frontier model using copula: application to intercrop coffee production in Northern Thailand (2015)
  13. Kauermann, Göran; Schellhase, Christian: Flexible pair-copula estimation in D-vines using bivariate penalized splines (2014)
  14. Czado, Claudia; Brechmann, Eike Christian; Gruber, Lutz: Selection of vine copulas (2013)
  15. Eike Brechmann; Ulf Schepsmeier: Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine (2013)
  16. Krämer, Nicole; Brechmann, Eike C.; Silvestrini, Daniel; Czado, Claudia: Total loss estimation using copula-based regression models (2013)