On efficient probability forecasting systems

We study the asymptotic behaviour of probability forecasting systems, and discuss their usefulness as inferential tools for statistical problems such as model verification and selection. Our theoretical setting is the prequential, or predictive sequential, framework proposed by Dawid (1984). We stud...

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Veröffentlicht in:Biometrika 1999-12, Vol.86 (4), p.765-784
Hauptverfasser: Skouras, K, Dawid, AP
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Dawid, AP
description We study the asymptotic behaviour of probability forecasting systems, and discuss their usefulness as inferential tools for statistical problems such as model verification and selection. Our theoretical setting is the prequential, or predictive sequential, framework proposed by Dawid (1984). We study especially the notion of prequential efficiency of a forecasting system and present some new results. We focus on plug-in, or estimative, forecasting systems, where the forecast distribution is generated by replacing the unknown parameter with an estimate.
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subjects Bayesian forecasting system
Efficiency
Efficiency metrics
estimative predictive distribution
Estimators
Exact sciences and technology
Forecasting
Forecasting models
Mathematical foundations
Mathematics
Maximum likelihood estimators
Performance evaluation
plug-in predictive distribution
Point forecasts
predictive inference
prequential inference
Probabilities
Probability and statistics
Probability forecasts
Sciences and techniques of general use
statistical forecasting system
Statistical forecasts
Statistical theories
Statistical variance
Statistics
Validity
title On efficient probability forecasting systems
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