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Rehms, Raphael 
ORCID: https://orcid.org/0000-0002-3996-0194; Ellenbach, Nicole; Rehfuess, Eva ORCID: https://orcid.org/0000-0002-4318-8846; Burns, Jacob ORCID: https://orcid.org/0000-0003-4015-6862; Mansmann, Ulrich ORCID: https://orcid.org/0000-0002-9955-8906 und Hoffmann, Sabine ORCID: https://orcid.org/0000-0001-6197-8801
(2024):
A Bayesian hierarchical approach to account for evidence and uncertainty in the modeling of infectious diseases: An application to COVID‐19.
In: Biometrical Journal, Bd. 66, Nr. 1
[PDF, 2MB]
ORCID: https://orcid.org/0000-0002-3996-0194; Ellenbach, Nicole; Rehfuess, Eva ORCID: https://orcid.org/0000-0002-4318-8846; Burns, Jacob ORCID: https://orcid.org/0000-0003-4015-6862; Mansmann, Ulrich ORCID: https://orcid.org/0000-0002-9955-8906 und Hoffmann, Sabine ORCID: https://orcid.org/0000-0001-6197-8801
(2024):
A Bayesian hierarchical approach to account for evidence and uncertainty in the modeling of infectious diseases: An application to COVID‐19.
In: Biometrical Journal, Bd. 66, Nr. 1
[PDF, 2MB]
Ellenbach, Nicole; Boulesteix, Anne-Laure; Bischl, Bernd; Unger, Kristian und Hornung, Roman
(2020):
Improved Outcome Prediction Across Data Sources Through Robust Parameter Tuning.
In: Journal of Classification, Bd. 38: S. 212-231
[PDF, 709kB]