Dear all,
It is my pleasure to announce the following CWI Machine Learning seminar.
Speaker: Johanna Ziegel (University of Bern) Title: Valid sequential inference on probability forecast performance Date: Friday 10 September, 14:00 Location: CWI L016 and on Zoom (link will follow)
This seminar will be held live at reduced capacity, and will be live-streamed on zoom for remote attendance.
Please find the abstract below.
Hope to see you then.
Best wishes,
Wouter
Details:
https://portals.project.cwi.nl/ml-reading-group/events/valid-sequential-infe...
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Valid sequential inference on probability forecast performance
Johanna Ziegel (University of Bern)
Probability forecasts for binary events play a central role in many applications. Their quality is commonly assessed with proper scoring rules, which assign forecasts a numerical score such that a correct forecast achieves a minimal expected score. In this paper, we construct e-values for testing the statistical significance of score differences of competing forecasts in sequential settings. E-values have been proposed as an alternative to p-values for hypothesis testing, and they can easily be transformed into conservative p-values by taking the multiplicative inverse. The e-values proposed in this article are valid in finite samples without any assumptions on the data generating processes. They also allow optional stopping, so a forecast user may decide to interrupt evaluation taking into account the available data at any time and still draw statistically valid inference, which is generally not true for classical p-value based tests. In a case study on postprocessing of precipitation forecasts, state-of-the-art forecasts dominance tests and e-values lead to the same conclusions.