Probabilistic forecasts, calibration and sharpness

• Published in: Journal of the Royal Statistical Society. Series B, Statistical methodology Vol. 69; no. 2; pp. 243 - 268
• Main Authors: Gneiting, Tilmann, Balabdaoui, Fadoua, Raftery, Adrian E
• Format: Journal Article
• Language: English
• Published: Oxford, UK Oxford, UK : Blackwell Publishing Ltd 01.04.2007; Blackwell Publishing Ltd; Blackwell Publishers; Blackwell; Royal Statistical Society; Oxford University Press
• Series: Journal of the Royal Statistical Society Series B
• Subjects: Analytical forecasting; Autocorrelation; Calibration; Cross-validation; cumulative distribution; Density forecast; diagnostic techniques; Distribution; Distribution theory; Ensemble prediction system; Evaluation; Ex post evaluation; Exact sciences and technology; Forecast verification; Forecasting; Forecasts; Histograms; Inference from stochastic processes; time series analysis; Mathematical methods; Mathematics; Model diagnostics; Model testing; Nonparametric inference; Posterior predictive assessment; prediction; Predictive distribution; Prequential principle; Probabilities; Probability; Probability and statistics; Probability forecasts; Probability integral transform; Probability theory and stochastic processes; Proper scoring rule; Sciences and techniques of general use; Statistical analysis; Statistical methods; Statistics; Stochastic processes; Studies; Time series; time series analysis; Time series forecasting; United States; Weather forecasting; Wind power; wind speed; Wind velocity; United States; Performance evaluation; Rank statistic; Density estimation; Histogram; Predictive distribution; Non parametric estimation; Cross validation; Forecast model; Hypothesis test; Probabilistic assessment; Posterior predictive assessment; Model matching; Cross-validation; Forecast verification; Ex post evaluation; Integral transformation; Posterior distribution; Density forecast; Model selection; Time series; Ensemble prediction system; Prequential principle; Proper scoring rule; Statistical method; Model diagnostics; Probability integral transform

Probabilistic forecasts of continuous variables 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 distribution...