用尺寸依赖的临界值校准扫描统计量：理论、方法和计算
Calibrating the scan statistic with size-dependent critical values: heuristics, methodology and computation
摘要：
已知具有可变窗口大小的扫描统计量有利于检测具有小空间范围的信号，并且对于具有大空间范围的信号存在相应的功率损失。最近的结果表明，这种损失并非不可避免：使用取决于窗口大小的临界值可以同时对所有信号大小进行最佳检测，因此不知道正确的窗口大小和使用可变的窗口大小进行扫描不会付出很大的代价。本文给出了这样的大小依赖的临界值，其应用程序的各种设置，包括多变量的情况下，和最近的结果有关的快速算法计算扫描统计的算法和方法的审查。
英文摘要：
It is known that the scan statistic with variable window size favors the detection of signals with small spatial extent and there is a corresponding loss of power for signals with large spatial extent. Recent results have shown that this loss is not inevitable: Using critical values that depend on the size of the window allows optimal detection for all signal sizes simultaneously, so there is no substantial price to pay for not knowing the correct window size and for scanning with a variable window size. This paper gives a review of the heuristics and methodology for such size-dependent critical values, their applications to various settings including the multivariate case, and recent results about fast algorithms for computing scan statistics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
