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  • 标题:Estimation of the global mode of a density: Minimaxity, adaptation, and computational complexity
  • 本地全文:下载
  • 作者:Ery Arias-Castro ; Wanli Qiao ; Lin Zheng
  • 期刊名称:Electronic Journal of Statistics
  • 印刷版ISSN:1935-7524
  • 出版年度:2022
  • 卷号:16
  • 期号:1
  • 页码:2774-2795
  • DOI:10.1214/21-EJS1972
  • 语种:English
  • 出版社:Institute of Mathematical Statistics
  • 摘要:We consider the estimation of the global mode of a density under some decay rate condition around the global mode. We show that the maximum of a histogram, with proper choice of bandwidth, achieves the minimax rate that we establish for the setting that we consider. This is based on knowledge of the decay rate. To address the situation where the decay rate is unknown, we propose a multiscale variant consisting in the recursive refinement of a histogram. We show that this variant is minimax adaptive. These methods run in linear time, and we prove in an appendix that this is best possible: There is no estimation procedure running in sublinear time that achieves the minimax rate.
  • 关键词:histogram-based estimation;minimax adaptive;mode estimation;multiscale estimation
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