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Local Proper Scoring Rules
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ehm, Werner Gneiting, Tilmann |
| Copyright Year | 2009 |
| Abstract | Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score based on the predictive distribution and on the event or value that materializes. A scoring rule is proper if it encourages truthful reporting. It is local of orderif the score depends on the predictive density only through its value and its derivatives of order up toat the observation. Previously, only a single local proper scoring rule had been known, namely the logarithmic score, which is local of order � = 0. Here we introduce the Fisher score, which is a local proper scoring rule of order � = 2. It relates to the Fisher information in the same way that the logarithmic score relates to the Kullback-Leibler information. The convex cone generated by the logarithmic score and the Fisher score exhausts the class of the local proper scoring rules of order � ≤ 2, up to equivalence and regularity conditions. In a data example, we use local and non-local proper scoring rules to assess statistically postprocessed ensemble weather forecasts. Finally, we develop a multivariate version of the Fisher score. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.stat.washington.edu/research/reports/2009/tr551.pdf |
| Alternate Webpage(s) | http://www.stat.washington.edu/www/research/reports/2009/tr551.pdf |
| Alternate Webpage(s) | https://www.stat.washington.edu/research/reports/2009/tr551.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
