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  • 标题:Lower large deviations for geometric functionals
  • 本地全文:下载
  • 作者:Christian Hirsch ; Benedikt Jahnel ; András Tóbiás
  • 期刊名称:Electronic Communications in Probability
  • 印刷版ISSN:1083-589X
  • 出版年度:2020
  • 卷号:25
  • DOI:10.1214/20-ECP322
  • 语种:English
  • 出版社:Electronic Communications in Probability
  • 摘要:This work develops a methodology for analyzing large-deviation lower tails associated with geometric functionals computed on a homogeneous Poisson point process. The technique applies to characteristics expressed in terms of stabilizing score functions exhibiting suitable monotonicity properties. We apply our results to clique counts in the random geometric graph, intrinsic volumes of Poisson–Voronoi cells, as well as power-weighted edge lengths in the random geometric, $k$-nearest neighbor and relative neighborhood graph.
  • 关键词:large deviations; lower tails; stabilizing functionals; random geometric graph; $k$-nearest neighbor graph; relative neighborhood graph; Voronoi tessellation; clique count
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