T. Nagler, T. Vatter. Solving estimating equations with copulas. [pdf]

Journal and conference papers


T. Nguyen-Huy, J. Kath, T. Nagler, Y. Khaung, T.S.S. Aung, S. Mushtaq, T. Marcussen, R. Stone. A satellite-based Standardized Antecedent Precipitation Index (SAPI) for mapping extreme rainfall risk in Myanmar. Remote Sensing Applications: Society and Environment, 26 [doi] [pdf]

T. Nagler, D. Krüger, A. Min. Stationary vine copula models for multivariate time series. Journal of Econometrics, 227(2), pp. 305-324 [doi] [pdf] [suppl.]

C. Czado, T. Nagler. Vine copula based modeling. Annual Review of Statistics and Its Application 9, pp. 453-477 [doi] [pdf]


D. Meyer, T. Nagler. Synthia: multidimensional synthetic data generation in Python. Journal of Open Source Software, 6(65), 2863 [doi] [pdf]

D. Meyer, T. Nagler, R.J. Hogan. Copula-based synthetic data augmentation for machine learning emulators. Geoscientific Model Development 14(8):5205–5215 [doi] [pdf]

K. Aas, T. Nagler, M. Jullum, A. Løland. Explaining predictive models using Shapley values and non-parametric vine copulas. Dependence Modeling, 9:62–81 [doi] [pdf]

T. Nagler. R-friendly multi-threading in C++. Journal of Statistical Software, 97(c1) [doi] [pdf]


R. Vio, T. Nagler, P. Andreani. Modeling high-dimensional dependence among astronomical data. Astronomy & Astrophysics, 642, A156 [doi] [pdf]

T.K. Eggersmann, P. Baumeister, J. Kumbringk, D. Mayr, E. Schmoeckel, C.J. Thaler, C. Dannecker, U. Jeschke, T. Nagler, S. Mahner, K. Sharaf, J.K.S. Gallwas. Oropharyngeal HPV Detection Techniques in HPV-associated Head and Neck Cancer Patients. Anticancer Research, 40(4):2117-2123 [doi]


T. Nagler, C. Bumann, C. Czado. Model selection for sparse high-dimensional vine copulas with application to portfolio risk. Journal of Multivariate Analysis, 172: 180-192 [doi] [pdf]

W.S. Jäger, T. Nagler, C. Czado, R.T. McCall. A statistical simulation method for joint time series of non-stationary hourly wave parameters. Coastal Engineering, 146: 14-31 [doi] [pdf]


J. Urbano, T. Nagler. Stochastic simulation of test collections: evaluation scores. The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, p. 695-704 [doi] [pdf]

L. Höhndorf, T. Nagler, P. Koppitz, C. Czado, F. Holzapfel. Statistical dependence analyses of operational flight data used for landing reconstruction enhancement. The 22nd Air Transport Research Society World Conference

T. Vatter and T. Nagler. Generalized additive models for pair-copula constructions. Journal of Computational and Graphical Statistics, 27(4): 715-727 [doi] [pdf]

T. Nagler. A generic approach to nonparametric function estimation with mixed data. Statistics & Probability Letters, 137:326–330 [doi] [pdf]

T. Nagler. Asymptotic analysis of the jittering kernel density estimator. Mathematical Methods of Statistics, 27(1): 32-46 [doi] [pdf]

T. Nagler. kdecopula: An R package for the kernel estimation of copula densities. Journal of Statistical Software, 48(7) [doi] [pdf]


T. Nagler, Schellhase, C. and C. Czado. Nonparametric estimation of simplified vine copula models: comparison of methods. Dependence Modeling, 5:99-120 [doi] [pdf]


T. Nagler. C. Czado. Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas. Journal of Multivariate Analysis, 151:69-89 [doi] [pdf]



C. Czado, D. Müller, T. Nagler. Dependence modelling in ultra high dimensions with vine copulas.
Book chapter in High Performance Computing in Science and Engineering - on the Tier-2 System CoolMUC; Garching/Munich 2018 [pdf]

A. Möller, L. Spazzini, D. Kraus, T. Nagler, C. Czado. Vine copula based post-processing of ensemble forecasts for temperature. Research report [pdf]

N. Schallhorn, D. Kraus, T. Nagler and C. Czado. D-vine quantile regression with discrete variables. Research report [pdf]

T. Nagler. Nonparametric estimation in simplified vine copula models. PhD thesis, Technical University of Munich [pdf]


T. Nagler. Comment on “A coupled stochastic rainfall-evapotranspiration model for hydrological impact analysis” by Minh Tu Pham et al. Interactive comment on Hydrol. Earth Syst. Sci. Discuss. [doi] [pdf]

A. Kreuzer, T. Nagler, C. Czado. Heavy tailed spatial autocorrelation models. Research report [pdf]


T. Nagler. Kernel methods for vine copula estimation. Master’s thesis, Technical University of Munich [pdf]