On efficient probability forecasting systems

• 成果类型: Article
• 署名作者: Skouras, K; Dawid, AP
• 署名单位: University of London; University College London
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/86.4.765
• 发表日期: 1999
• 页码: 765784
• 关键词: predictive-distributions; stochastic complexity; exponential-families; model selection; fit

摘要

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.