4.6 Article

Evaluation of point forecasts for extreme events using consistent scoring functions

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WILEY
DOI: 10.1002/qj.4206

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consistent scoring function; decision theory; forecast ranking; forecast verification; point forecast; proper scoring rule; rare and extreme events

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This article introduces a method for comparing point forecasts in a region of interest, emphasizing the importance of performance in the selected region of the variable's range, providing a natural interpretation rooted in optimal decision theory.
We present a method for comparing point forecasts in a region of interest, such as the tails or centre of a variable's range. This method cannot be hedged, in contrast to selecting events conditionally to evaluate and then using a scoring function that would have been consistent (or proper) prior to event selection. Our method also gives decompositions of scoring functions that are consistent for the mean or a particular quantile or expectile. Each member of each decomposition is itself a consistent scoring function that emphasises performance over a selected region of the variable's range. The score of each member of the decomposition has a natural interpretation rooted in optimal decision theory. It is the weighted average of economic regret over user decision thresholds, where the weight emphasises those decision thresholds in the corresponding region of interest.

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