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Biometrika 1999 86(4):765-784; doi:10.1093/biomet/86.4.765
© 1999 by Biometrika Trust
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On efficient probability forecasting systems

K SkourasA1 and AP DawidA2

Department of Statistical Science, University College London, Gower Street, London WC1E 6BT, UK A1 E-mail: skouras@stats.ucl.ac.uk A2 E-mail: dawid@stats.ucl.ac.uk

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.

Key Words: Bayesian forecasting system; efficiency; estimative predictive distribution; forecasting; plug-in predictive distribution; predictive inference; prequential inference; statistical forecasting system


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