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122 Publications visible to you, out of a total of 122
Learning to forecast: The Probabilistic Time Series Forecasting Challenge

Abstract

Not specified

Authors: Johannes Bracher, Nils Koster, Fabian Krüger, Sebastian Lerch

Date Published: 1st Feb 2024

Publication Type: Journal

Comparative evaluation of point process forecasts

Abstract

Not specified

Authors: Jonas R. Brehmer, Tilmann Gneiting, Marcus Herrmann, Warner Marzocchi, Martin Schlather, Kirstin Strokorb

Date Published: 1st Feb 2024

Publication Type: Journal

Scalable stellar evolution forecasting — Deep learning emulation versus hierarchical nearest-neighbor interpolation

Abstract

Not specified

Authors: K. Maltsev, F. R. N. Schneider, F. K. Röpke, A. I. Jordan, G. A. Qadir, W. E. Kerzendorf, K. Riedmiller, P. van der Smagt

Date Published: 19th Jan 2024

Publication Type: Journal

Decompositions of the mean continuous ranked probability score

Abstract

Not specified

Authors: Sebastian Arnold, Eva-Maria Walz, Johanna Ziegel, Tilmann Gneiting

Date Published: 2024

Publication Type: Journal

Postprocessing of ensemble weather forecasts using permutation-invariant neural networks

Abstract

Not specified

Authors: Kevin Höhlein, Benedikt Schulz, Rüdiger Westermann, Sebastian Lerch

Date Published: 2024

Publication Type: Journal

Automatic miscalibration diagnosis: Interpreting probability integral transform (PIT) histograms

Abstract

Not specified

Authors: Ondřej Podsztavek, Alexander I. Jordan, Pavel Tvrdík, Kai L. Polsterer

Date Published: 2024

Publication Type: Journal

Why are different estimates of the effective reproductive number so different? A case study on COVID-19 in Germany

Abstract (Expand)

tive reproductive number Rt has taken a central role in the scientific, political, and public discussion during the COVID-19 pandemic, with numerous real-time estimates of this quantity routinely … published. Disagreement between estimates can be substantial and may lead to confusion among decision-makers and the general public. In this work, we compare different estimates of the national-level effective reproductive number of COVID-19 in Germany in 2020 and 2021. We consider the agreement between estimates from the same method but published at different time points (within-method agreement) as well as retrospective agreement across eight different approaches (between-method agreement). Concerning the former, estimates from some methods are very stable over time and hardly subject to revisions, while others display considerable fluctuations. To evaluate between-method agreement, we reproduce the estimates generated by different groups using a variety of statistical approaches, standardizing analytical choices to assess how they contribute to the observed disagreement. These analytical choices include the data source, data pre-processing, assumed generation time distribution, statistical tuning parameters, and various delay distributions. We find that in practice, these auxiliary choices in the estimation of Rt may affect results at least as strongly as the selection of the statistical approach. They should thus be communicated transparently along with the estimates.

Authors: Elisabeth K. Brockhaus, Daniel Wolffram, Tanja Stadler, Michael Osthege, Tanmay Mitra, Jonas M. Littek, Ekaterina Krymova, Anna J. Klesen, Jana S. Huisman, Stefan Heyder, Laura M. Helleckes, Matthias an der Heiden, Sebastian Funk, Sam Abbott, Johannes Bracher

Date Published: 27th Nov 2023

Publication Type: Journal

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