The robust scale estimator Q_n developed by Croux and Rousseeuw [3], for the computation of which they provided a deterministic algorithm, has proven to be very useful in several domains including in quality management and time series analysis. It has interesting mathematical (50% breakdown, 82% Asymptotic Relative Efficiency) and computing (O(nlogn) time, O(n) space) properties. While working on a faster algorithm to compute Q_n, we have discovered an error in the computation of the d constant, and as a consequence in the d_n constants that are used to scale the statistic for consistency with the variance of a normal sample. These errors have been reproduced in several articles including in the International Standard Organisation 13,528 [12] document. In this article, we fix the errors and present a new approach, which includes a new algorithm, allowing computations to run 1.3 to 4.5 times faster when n grows from 10 to 100,000.

由 Croux 和 Rousseeuw [3] 开发的鲁棒尺度估计器Q _n，他们提供了一种确定性算法用于计算，已被证明在包括质量管理和时间序列分析在内的多个领域非常有用。它具有有趣的数学（50% 故障，82% 渐近相对效率）和计算（O(nlogn)时间，O ( n ) 空间）属性。在研究计算Q _n的更快算法时，我们发现d常数的计算存在错误，因此d _n用于缩放统计量以与正常样本的方差保持一致的常量。这些错误已在多篇文章中重现，包括国际标准组织 13,528 [12] 文档。在本文中，我们修复了错误并提出了一种新方法，其中包括一种新算法，当n从 10 增长到 100,000时，计算速度可以提高 1.3 到 4.5 倍。