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Claudia Czado
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- affiliation: Technical University Munich, Germany
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2020 – today
- 2025
- [j26]Claudia Czado:
Vine copula based structural equation models. Comput. Stat. Data Anal. 203: 108076 (2025) - 2024
- [j25]Hassan Alnasser, Marco Pfahler, Ariane Hanebeck, Lukas Beller, Claudia Czado:
D-Vine-Based Correction of Physics-Based Model Output for the Identification of Risky Flights With Respect to Runway Overruns. IEEE Access 12: 129173-129186 (2024) - 2023
- [j24]Alexander Kreuzer, Luciana Dalla Valle, Claudia Czado:
Bayesian multivariate nonlinear state space copula models. Comput. Stat. Data Anal. 188: 107820 (2023) - 2022
- [c2]Ariane Hanebeck, Claudia Czado:
On the Observability of Gaussian Models using Discrete Density Approximations. FUSION 2022: 1-8 - [i1]Ariane Hanebeck, Claudia Czado:
On the Observability of Gaussian Models using Discrete Density Approximations. CoRR abs/2208.08870 (2022) - 2020
- [j23]Nicole Barthel, Claudia Czado, Yarema Okhrin:
A partial correlation vine based approach for modeling and forecasting multivariate volatility time-series. Comput. Stat. Data Anal. 142 (2020) - [j22]Xiaolong Wang, Lukas Beller, Claudia Czado, Florian Holzapfel:
Modeling of Stochastic Wind Based on Operational Flight Data Using Karhunen-Loève Expansion Method. Sensors 20(16): 4634 (2020)
2010 – 2019
- 2019
- [j21]Dominik Müller, Claudia Czado:
Dependence modelling in ultra high dimensions with vine copulas and the Graphical Lasso. Comput. Stat. Data Anal. 137: 211-232 (2019) - [j20]Thomas Nagler, C. Bumann, Claudia Czado:
Model selection in sparse high-dimensional vine copula models with an application to portfolio risk. J. Multivar. Anal. 172: 180-192 (2019) - [j19]Dominik Müller, Claudia Czado:
Selection of sparse vine copulas in high dimensions with the Lasso. Stat. Comput. 29(2): 269-287 (2019) - 2018
- [j18]Nicole Barthel, Candida Geerdens, Matthias Killiches, Paul Janssen, Claudia Czado:
Vine copula based likelihood estimation of dependence patterns in multivariate event time data. Comput. Stat. Data Anal. 117: 109-127 (2018) - [j17]Matthias Killiches, Daniel Kraus, Claudia Czado:
Model distances for vine copulas in high dimensions. Stat. Comput. 28(2): 323-341 (2018) - 2017
- [j16]Anastasios Panagiotelis, Claudia Czado, Harry Joe, Jakob Stöber:
Model selection for discrete regular vine copulas. Comput. Stat. Data Anal. 106: 138-152 (2017) - [j15]Daniel Kraus, Claudia Czado:
D-vine copula based quantile regression. Comput. Stat. Data Anal. 110: 1-18 (2017) - 2016
- [j14]Thomas Nagler, Claudia Czado:
Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas. J. Multivar. Anal. 151: 69-89 (2016) - [c1]Guilherme Pereira, Álvaro Veiga, Tobias Michael Erhardt, Claudia Czado:
Spatial R-vine copula for streamflow scenario simulation. PSCC 2016: 1-7 - 2015
- [j13]Jakob Stöber, Hyokyoung Grace Hong, Claudia Czado, Pulak Ghosh:
Comorbidity of chronic diseases in the elderly: Patterns identified by a copula design for mixed responses. Comput. Stat. Data Anal. 88: 28-39 (2015) - [j12]Harry Joe, Jun Cai, Claudia Czado, Haijun Li:
Preface to special issue on high-dimensional dependence and copulas. J. Multivar. Anal. 138: 1-3 (2015) - [j11]Tobias Michael Erhardt, Claudia Czado, Ulf Schepsmeier:
Spatial composite likelihood inference using local C-vines. J. Multivar. Anal. 138: 74-88 (2015) - [j10]Carole Bernard, Claudia Czado:
Conditional quantiles and tail dependence. J. Multivar. Anal. 138: 104-126 (2015) - 2014
- [j9]Aleksey Min, Claudia Czado:
SCOMDY models based on pair-copula constructions with application to exchange rates. Comput. Stat. Data Anal. 76: 523-535 (2014) - [j8]Jakob Stöber, Claudia Czado:
Regime switches in the dependence structure of multidimensional financial data. Comput. Stat. Data Anal. 76: 672-686 (2014) - 2013
- [j7]J. Dißmann, Eike C. Brechmann, Claudia Czado, Dorota Kurowicka:
Selecting and estimating regular vine copulae and application to financial returns. Comput. Stat. Data Anal. 59: 52-69 (2013) - [j6]Jakob Stöber, Harry Joe, Claudia Czado:
Simplified pair copula constructions - Limitations and extensions. J. Multivar. Anal. 119: 101-118 (2013) - 2012
- [j5]Carlos Almeida, Claudia Czado:
Efficient Bayesian inference for stochastic time-varying copula models. Comput. Stat. Data Anal. 56(6): 1511-1527 (2012) - 2011
- [j4]Ran Zhang, Claudia Czado, Aleksey Min:
Efficient maximum likelihood estimation of copula based meta t-distributions. Comput. Stat. Data Anal. 55(3): 1196-1214 (2011) - [j3]Claudia Czado, Anette Heyn, Gernot Müller:
Modeling individual migraine severity with autoregressive ordered probit models. Stat. Methods Appl. 20(1): 101-121 (2011) - 2010
- [j2]Aleksey Min, Hajo Holzmann, Claudia Czado:
Model selection strategies for identifying most relevant covariates in homoscedastic linear models. Comput. Stat. Data Anal. 54(12): 3194-3211 (2010)
2000 – 2009
- 2008
- [j1]Susanne Gschlößl, Claudia Czado:
Does a Gibbs sampler approach to spatial Poisson regression models outperform a single site MH sampler? Comput. Stat. Data Anal. 52(9): 4184-4202 (2008)
Coauthor Index
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