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  • 标题:Asymptotic minimum scoring rule prediction
  • 本地全文:下载
  • 作者:Federica Giummolè ; Valentina Mameli
  • 期刊名称:Electronic Journal of Statistics
  • 印刷版ISSN:1935-7524
  • 出版年度:2018
  • 卷号:12
  • 期号:2
  • 页码:2401-2429
  • DOI:10.1214/18-EJS1454
  • 语种:English
  • 出版社:Institute of Mathematical Statistics
  • 摘要:Most of the methods nowadays employed in forecast problems are based on scoring rules. There is a divergence function associated to each scoring rule, that can be used as a measure of discrepancy between probability distributions. This approach is commonly used in the literature for comparing two competing predictive distributions on the basis of their relative expected divergence from the true distribution.
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