# Research

## Preprints

**Nagler, T.**, Krüger, D., Min, A.

Stationary vine copula models for multivariate time series

Meyer, D., **Nagler, T.**, Hogan, R.J.

Copula-based synthetic data generation for machine learning emulators in weather and climate: application to a simple radiation model

Meyer, D., **Nagler, T.**

Synthia: multidimensional synthetic data generation in Python

**Nagler, T.**, Vatter, T.

Solving estimating equations with copulas

## Journal and conference papers

Czado, C. and **Nagler, T.** (2021)

Vine copula based modeling

*Annual Review of Statistics and Its Application, to appear*

Aas, K., **Nagler, T.**, Jullum, M., Løland, A. (2021)

Explaining predictive models using Shapley values and non-parametric vine copulas

*Dependence Modeling, to appear*

**Nagler, T.** (2021)

R-friendly multi-threading in C++

*Journal of Statistical Software, 97(c1)*

Vio, R., **Nagler, T.**, Andreani, P. (2020)

Modeling high-dimensional dependence among astronomical data

*Astronomy & Astrophysics, 642, A156*

Eggersmann, T.K., Baumeister, P., Kumbringk, J., Mayr, D., Schmoeckel, E., Thaler, C.J., Dannecker, C., Jeschke, U., **Nagler, T.**, Mahner, S., Sharaf, K., and Gallwas, J.K.S. (2020)

Oropharyngeal HPV Detection Techniques in HPV-associated Head and Neck Cancer Patients.

*Anticancer Research, 40(4):2117-2123*

**Nagler, T.**, Bumann, C., Czado, C. (2019)

Model selection for sparse high-dimensional vine copulas with application to
portfolio risk

*Journal of Multivariate Analysis, 172: 180-192*
[doi]

Jäger, W.S., **Nagler, T.**, Czado, C., McCall, R.T. (2019)

A statistical simulation method for joint time series of non-stationary hourly wave parameters

*Coastal Engineering, 146: 14-31*
[doi]

Urbano, J., **Nagler, T.** (2018)

Stochastic simulation of test collections: evaluation scores

*The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, p. 695-704*
[doi]

Höhndorf, L., **Nagler, T.**, Koppitz, P., Czado, C., Holzapfel, F. (2018)

Statistical dependence analyses of operational flight data used for landing
reconstruction enhancement

*22nd ATRS World Conference*

Vatter, T. and **Nagler, T.** (2018)

Generalized additive models for pair-copula constructions

*Journal of Computational and Graphical Statistics, 27(4): 715-727*
[doi]

**Nagler, T.** (2018)

A generic approach to nonparametric function estimation with mixed data

*Statistics & Probability Letters, 137:326–330*
[doi]

**Nagler, T.** (2018)

Asymptotic analysis of the jittering kernel density estimator

*Mathematical Methods of Statistics, 27(1): 32-46*
[doi]

**Nagler, T.** (2018)

kdecopula: An R package for the kernel estimation of copula densities

*Journal of Statistical Software, 48(7)*
[doi]

**Nagler, T.**, Schellhase, C. and Czado, C. (2017)

Nonparametric estimation of simplified vine copula models: comparison of
methods

*Dependence Modeling, 5:99-120*
[doi]

**Nagler, T.** and Czado, C. (2016)

Evading the curse of dimensionality in nonparametric density estimation with
simplified vine copulas

*Journal of Multivariate Analysis, 151:69-89*
[doi]

## Other

Czado, C., Müller, D., **Nagler, T.** (2018)

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*

Möller, A., Spazzini, L., Kraus, D., **Nagler, T.**, Czado, C.

Vine copula based post-processing of ensemble forecasts for temperature

*Research report*

Schallhorn, N., Kraus, D., **Nagler, T.** and Czado, C.

D-vine quantile regression with discrete variables

*Research report*

**Nagler, T.** (2018)

Nonparametric estimation in simplified vine copula models

*PhD thesis, Technical University of Munich*

**Nagler, T.** (2017)

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]

**Nagler, T.** (2014)

Kernel methods for vine copula estimation

*Master’s thesis, Technical University of Munich*