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The world of vines: An interview with Claudia Czado

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  • Genest Christian

    (Department of Mathematics and Statistics, McGill University, Montréal (Québec) Canada.)

  • Scherer Matthias

    (Lehrstuhl für Finanzmathematik, Technische Universität München, Garching, Germany.)

Abstract

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Suggested Citation

  • Genest Christian & Scherer Matthias, 2019. "The world of vines: An interview with Claudia Czado," Dependence Modeling, De Gruyter, vol. 7(1), pages 169-180, January.
    • Handle: RePEc:vrs:demode:v:7:y:2019:i:1:p:169-180:n:8
    DOI: 10.1515/demo-2019-0008
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    References listed on IDEAS

    as
    1. Kurowicka, D. & Cooke, R.M., 2007. "Sampling algorithms for generating joint uniform distributions using the vine-copula method," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2889-2906, March.
    2. Anastasios Panagiotelis & Claudia Czado & Harry Joe, 2012. "Pair Copula Constructions for Multivariate Discrete Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(499), pages 1063-1072, September.
    3. Dißmann, J. & Brechmann, E.C. & Czado, C. & Kurowicka, D., 2013. "Selecting and estimating regular vine copulae and application to financial returns," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 52-69.
    4. Müller, Dominik & Czado, Claudia, 2019. "Dependence modelling in ultra high dimensions with vine copulas and the Graphical Lasso," Computational Statistics & Data Analysis, Elsevier, vol. 137(C), pages 211-232.
    5. Axel Munk & Claudia Czado, 1998. "Nonparametric validation of similar distributions and assessment of goodness of fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(1), pages 223-241.
    6. Kraus, Daniel & Czado, Claudia, 2017. "D-vine copula based quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 1-18.
    7. Stöber, Jakob & Czado, Claudia, 2014. "Regime switches in the dependence structure of multidimensional financial data," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 672-686.
    8. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    9. Nicole Barthel & Candida Geerdens & Claudia Czado & Paul Janssen, 2019. "Dependence modeling for recurrent event times subject to right‐censoring with D‐vine copulas," Biometrics, The International Biometric Society, vol. 75(2), pages 439-451, June.
    10. Acar, Elif F. & Genest, Christian & Nešlehová, Johanna, 2012. "Beyond simplified pair-copula constructions," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 74-90.
    11. Stöber, Jakob & Hong, Hyokyoung Grace & Czado, Claudia & Ghosh, Pulak, 2015. "Comorbidity of chronic diseases in the elderly: Patterns identified by a copula design for mixed responses," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 28-39.
    12. Aleksey Min & Claudia Czado, 2010. "Bayesian Inference for Multivariate Copulas Using Pair-Copula Constructions," Journal of Financial Econometrics, Oxford University Press, vol. 8(4), pages 511-546, Fall.
    13. Matthias Killiches & Claudia Czado, 2018. "A D‐vine copula‐based model for repeated measurements extending linear mixed models with homogeneous correlation structure," Biometrics, The International Biometric Society, vol. 74(3), pages 997-1005, September.
    14. Erhardt, Tobias Michael & Czado, Claudia & Schepsmeier, Ulf, 2015. "Spatial composite likelihood inference using local C-vines," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 74-88.
    15. Nagler, Thomas & Czado, Claudia, 2016. "Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 151(C), pages 69-89.
    Full references (including those not matched with items on IDEAS)

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