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文章基本信息

  • 标题:Local Influence on Posterior Distributions under Multiplicative Modes of Perturbation
  • 本地全文:下载
  • 作者:Angelika van der Linde
  • 期刊名称:Bayesian Analysis
  • 印刷版ISSN:1931-6690
  • 电子版ISSN:1936-0975
  • 出版年度:2007
  • 卷号:2
  • 期号:2
  • 页码:319--332
  • 出版社:International Society for Bayesian Analysis
  • 摘要:Any unperturbed and perturbed posterior density can formally be linked by a mixture. Many divergences between the unperturbed and perturbed posterior density - global measures of inuence of the perturbation - are then essen- tially determined by the Fisher information with respect to the mixing parameter evaluated at the unperturbed density. It is investigated which aspect of change this Fisher information - commonly interpreted as local measure of inuence - captures in assessing inuence of the perturbation. Under multiplicative modes of perturbation it is nicely interpretable as unperturbed posterior variance of the (log-)perturbation function.
  • 关键词:Bayesian robustness, case deletion
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