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Malte S. Kurz
Malte S. Kurz
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Simplified vine copula models: Approximations based on the simplifying assumption
F Spanhel, MS Kurz
47*2019
Testing the simplifying assumption in high-dimensional vine copulas
MS Kurz, F Spanhel
Electronic Journal of Statistics 16 (2), 5226-5276, 2022
25*2022
Distributed Double Machine Learning with a Serverless Architecture
MS Kurz
Companion of the ACM/SPEC International Conference on Performance …, 2021
152021
The partial copula: Properties and associated dependence measures
F Spanhel, MS Kurz
Statistics & Probability Letters 119, 76-83, 2016
152016
DoubleML - An Object-Oriented Implementation of Double Machine Learning in R
P Bach, V Chernozhukov, MS Kurz, M Spindler
arXiv preprint arXiv:2103.09603, 2021
122021
DoubleML-An Object-Oriented Implementation of Double Machine Learning in Python.
P Bach, V Chernozhukov, MS Kurz, M Spindler
J. Mach. Learn. Res. 23, 53:1-53:6, 2022
112022
VineCopulaMatlab toolbox
M Kurz
URL https://github. com/MalteKurz/VineCopulaMatlab, 2016
11*2016
pacotest: Testing for Partial Copulas and the Simplifying Assumption in Vine Copulas
MS Kurz
R package version, 2017
72017
A note on low-dimensional Kalman smoothers for systems with lagged states in the measurement equation
MS Kurz
Economics Letters 168, 42-45, 2018
42018
DoubleML-Double Machine Learning in Python
P Bach, V Chernozhukov, MS Kurz, M Spindler
URL: https://github. com/DoubleML/doubleml-for-py, Python-Package version 0.1, 2020
22020
Vine copula based knockoff generation for high-dimensional controlled variable selection
MS Kurz
arXiv preprint arXiv:2210.11196, 2022
2022
Causal Inference with Machine Learning
V Chernozhukov, MD Cinelli, E Duflo, I Fernandez-Val, C Hansen, ...
2022
Risk Assessment and Spurious Seasonality
MS Kurz, S Mittnik
Econometrics and Statistics, 2022
2022
Dependence modeling with applications in financial econometrics
MS Kurz
lmu, 2018
2018
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