Authors : ... (Author of the conference)
... (Publisher )
Abstract :
Averages of proper scoring rules are often used to rank probabilistic forecasts. In many cases, the individual observations and their predictive distributions in these averages have variable scale (variance). I will show that some of the most popular proper scoring rules, such as the continuous ranked probability score (CRPS), up-weight observations with large uncertainty which can lead to unintuitive rankings. We have developed a new scoring rule, scaled CRPS (SCRPS), this new proper scoring rule is locally scale invariant and therefore works in the case of varying uncertainty.
I will demonstrate this how this affects model selection through parameter estimation in spatial statitics.
Keywords : Proper soring rules; model selection; prediction
MSC Codes :
60G25
- Prediction theory, See also {62M20}
62C25
- Compound decision problems
62M30
- Statistics of spatial processes
Additional resources :
https://www.cirm-math.fr/RepOrga/2146/Slides/Wallin.pdf
Language : English
Available date : 15/06/2020
Conference Date : 02/06/2020
Subseries : Research talks
arXiv category : Machine Learning ; Statistics Theory
Mathematical Area(s) : Probability & Statistics
Format : MP4 (.mp4) - HD
Video Time : 00:35:09
Targeted Audience : Researchers
Download : https://videos.cirm-math.fr/2020-06-02_Wallin.mp4
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Event Title : Mathematical Methods of Modern Statistics 2 / Méthodes mathématiques en statistiques modernes 2 Dates : 15/06/2020 - 19/06/2020
Event Year : 2020
Event URL : https://www.cirm-math.com/cirm-virtual-e...
DOI : 10.24350/CIRM.V.19644103
Cite this video as:
(2020). Scaling of scoring rules. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.19644103
URI : http://dx.doi.org/10.24350/CIRM.V.19644103
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See Also
Bibliography
- BOLIN, David et WALLIN, Jonas. Scale invariant proper scoring rules Scale dependence: Why the average CRPS often is inappropriate for ranking probabilistic forecasts. arXiv preprint arXiv:1912.05642, 2019. - https://arxiv.org/abs/1912.05642