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  • 标题:Uniform convergence rates for the approximated halfspace and projection depth
  • 本地全文:下载
  • 作者:Stanislav Nagy ; Rainer Dyckerhoff ; Pavlo Mozharovskyi
  • 期刊名称:Electronic Journal of Statistics
  • 印刷版ISSN:1935-7524
  • 出版年度:2020
  • 卷号:14
  • 期号:2
  • 页码:3939-3975
  • DOI:10.1214/20-EJS1759
  • 语种:English
  • 出版社:Institute of Mathematical Statistics
  • 摘要:The computational complexity of some depths that satisfy the projection property, such as the halfspace depth or the projection depth, is known to be high, especially for data of higher dimensionality. In such scenarios, the exact depth is frequently approximated using a randomized approach: The data are projected into a finite number of directions uniformly distributed on the unit sphere, and the minimal depth of these univariate projections is used to approximate the true depth. We provide a theoretical background for this approximation procedure. Several uniform consistency results are established, and the corresponding uniform convergence rates are provided. For elliptically symmetric distributions and the halfspace depth it is shown that the obtained uniform convergence rates are sharp. In particular, guidelines for the choice of the number of random projections in order to achieve a given precision of the depths are stated.
  • 关键词:approximation;depth;halfspace depth;projection depth;Tukey depth
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