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  • 标题:Adaptive Bayesian credible bands in regression with a Gaussian process prior
  • 本地全文:下载
  • 作者:Suzanne Sniekers ; Aad van der Vaart
  • 期刊名称:Sankhya. Series A, mathematical statistics and probability
  • 印刷版ISSN:0976-836X
  • 电子版ISSN:0976-8378
  • 出版年度:2019
  • 卷号:82
  • 期号:2
  • 页码:386-425
  • DOI:10.1007/s13171-019-00185-0
  • 出版社:Indian Statistical Institute
  • 摘要:Abstract A credible band is the set of all functions between a lower and an upper bound that are constructed so that the set has prescribed mass under the posterior distribution. In a Bayesian analysis such a band is used to quantify the remaining uncertainty on the unknown function in a similar manner as a confidence band. We investigate the validity of a credible band in the nonparametric regression model with the prior distribution on the function given by a Gaussian process. We show that there are many true regression functions for which the credible band has the correct order of magnitude to be used as a confidence set. We also exhibit functions for which the credible band is misleading.
  • 关键词:Credible band;Coverage;Uncertainty quantification;Nonparametric Bayes
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