Forecast Evaluation of Quantiles, Prediction Intervals, and other Set-Valued Functionals
| Autor: | Tobias Fissler, Jana Hlavinová, Birgit Rudloff, Rafael M. Frongillo |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Statistics and Probability 101029 Mathematische Statistik Mathematical optimization 62C05 62F07 62H11 91B06 Prediction interval Mathematics - Statistics Theory Statistics Theory (math.ST) Function (mathematics) 101029 Mathematical statistics Midpoint Methodology (stat.ME) Identification (information) Ranking consistency convex level sets elicitability Identifiability M-estimation prediction intervals random sets Vorob’ev quantiles FOS: Mathematics Identifiability Statistics Probability and Uncertainty Representation (mathematics) Statistics - Methodology Mathematics Quantile |
| Popis: | We introduce a theoretical framework of elicitability and identifiability of set-valued functionals, such as quantiles, prediction intervals, and systemic risk measures. A functional is elicitable if it is the unique minimiser of an expected scoring function, and identifiable if it is the unique zero of an expected identification function; both notions are essential for forecast ranking and validation, and $M$- and $Z$-estimation. Our framework distinguishes between exhaustive forecasts, being set-valued and aiming at correctly specifying the entire functional, and selective forecasts, content with solely specifying a single point in the correct functional. We establish a mutual exclusivity result: A set-valued functional can be either selectively elicitable or exhaustively elicitable or not elicitable at all. Notably, since quantiles are well known to be selectively elicitable, they fail to be exhaustively elicitable. We further show that the class of prediction intervals and Vorob'ev quantiles turn out to be exhaustively elicitable and selectively identifiable. In particular, we provide a mixture representation of elementary exhaustive scores, leading the way to Murphy diagrams. We give possibility and impossibility results for the shortest prediction interval and prediction intervals specified by an endpoint or a midpoint. We end with a comprehensive literature review on common practice in forecast evaluation of set-valued functionals. 46 pages, 2 figures. arXiv admin note: text overlap with arXiv:1907.01306 |
| Databáze: | OpenAIRE |
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