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Probabilistic forecasts, calibration and sharpness (2007)
| Content Provider | CiteSeerX |
|---|---|
| Author | Balabdaoui, Fadoua Gneiting, Tilmann Raftery, Adrian E. |
| Abstract | Probabilistic forecasts of a continuous variable take the form of predictive densities or predictive cumulative distribution functions. We propose a diagnostic approach to the evaluation of predictive performance that is based on the paradigm of maximizing the sharpness of the predictive distributions subject to calibration. Calibration refers to the statistical consistency between the distributional forecasts and the observations and is a joint property of the predictions and the events that materialize. Sharpness refers to the concentration of the predictive distributions and is a property of the forecasts only. A simple game-theoretic framework allows us to distinguish probabilistic calibration, exceedance calibration and marginal calibration. We propose and study tools for checking calibration and sharpness, among them the probability integral transform (PIT) histogram, marginal calibration plots, the sharpness diagram and proper scoring rules. The diagnostic approach is illustrated by an assessment and ranking of probabilistic forecasts of wind speed at the Stateline wind energy center in the US Pacific Northwest. In combination with cross-validation or in the time series context, our proposal provides very general, nonparametric alternatives to the use of information criteria for model diagnostics and model selection. Keywords: Cross-validation; Density forecast; Ensemble prediction system; Forecast verification; |
| File Format | |
| Journal | Journal of the Royal Statistical Society, Series B, Statistical Methodology |
| Publisher Date | 2007-01-01 |
| Access Restriction | Open |
| Subject Keyword | Exceedance Calibration U Pacific Northwest Time Series Context Forecast Verification Probabilistic Forecast Simple Game-theoretic Framework Sharpness Refers Distributional Forecast Predictive Performance Stateline Wind Energy Center Predictive Density Information Criterion Model Selection Ensemble Prediction System Probabilistic Calibration Joint Property Marginal Calibration Plot Model Diagnostics Proper Scoring Rule Nonparametric Alternative Predictive Distribution Predictive Cumulative Distribution Function Calibration Refers Marginal Calibration Sharpness Diagram Probability Integral Transform Diagnostic Approach Wind Speed Statistical Consistency |
| Content Type | Text |
| Resource Type | Article |
