Online Aggregation of Probabilistic Forecasts Based on the Continuous Ranked Probability Score
| Autor: | V. G. Trunov, V. V. V’yugin |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
010302 applied physics
Radiation Computer science Scoring rule Probabilistic logic Online aggregation 020206 networking & telecommunications 02 engineering and technology Function (mathematics) Condensed Matter Physics 01 natural sciences Outcome (probability) Electronic Optical and Magnetic Materials Distribution function 0103 physical sciences Statistics 0202 electrical engineering electronic engineering information engineering Probability distribution Electrical and Electronic Engineering |
| Zdroj: | Journal of Communications Technology and Electronics. 65:662-676 |
| ISSN: | 1555-6557 1064-2269 |
| Popis: | —Methods for generating predictions online and in the form of probability distributions of future outcomes are considered. The difference between the probabilistic forecast (probability distribution) and the numerical outcome is measured using the loss function (scoring rule). In practical statistics, the continuous ranked probability score (CRPS) is often used to estimate the discrepancy between probabilistic forecasts and (quantitative) outcomes. The paper considers the case when several competing methods (experts) give their online predictions as distribution functions. An algorithm is proposed for online aggregation of these distribution functions. The performance bounds of the proposed algorithm are obtained in the form of a comparison of the cumulative loss of the algorithm and the loss of expert hypotheses. Unlike existing estimates, the proposed estimates do not depend on time. The results of numerical experiments illustrating the proposed methods are presented. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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