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文章基本信息

  • 标题:Detection of outliers with a Bayesian hierarchical model: application to the single-grain luminescence dating method
  • 本地全文:下载
  • 作者:Jean-Michel Galharret ; Anne Philippe ; Norbert Mercier
  • 期刊名称:AEDOS
  • 印刷版ISSN:1984-5634
  • 出版年度:2021
  • 卷号:14
  • 期号:2
  • 页码:146-166
  • DOI:10.1285/i20705948v14n2p318
  • 语种:English
  • 出版社:AEDOS
  • 摘要:The event model was proposed by Lanos and Philippe (2018) to combine measurements in the context of archaeological chronological dating. We extend this model to luminescence dating and define a new strategy to detect outliers from the hyperparameters of the event model. This procedure is applied to the combination of Gaussian measurements and luminescence age estimation. We illustrate through simulations that it is preferable, in terms of accuracy and precision, to exclude detected outliers rather than use the robust estimation method (e.g. the event model).
  • 关键词:application to luminescence dating method;event hierarchical model;outliers
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