A robust scale estimator based on pairwise means
A robust scale estimator based on pairwise means
复制标题
基于成对均值的鲁棒尺度估计器
DOI：
10.1080/10485252.2011.621424
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
N. Weber
中科院分区：
文献类型：
--
作者：
Garth Tarr;S. Müller;N. Weber
我们提出了一种新的鲁棒尺度估计量，即成对均值尺度估计量pn，其最基本的形式是成对均值的四分位数范围。两两均值的使用在许多实际的分布中产生了惊人的高效率。在一个统一的广义l -统计框架下提出了pn的性质，该框架包含了许多其他的尺度估计。提出了对pn的扩展，包括取中间的范围τ×100%而不仅仅是成对均值的中间50%，以及对原始数据和成对均值进行修剪和Winsorising。此外，我们还实现了一种使用自适应修剪的方法，该方法实现了最大击穿值。在广泛的分布范围内，我们使用相应的最大似然估计作为比较的共同基础，研究了相对于许多其他已建立的鲁棒规模估计的两两平均规模估计的效率特性。
We propose a new robust scale estimator, the pairwise mean scale estimator P n , which in its most basic form is the interquartile range of the pairwise means. The use of pairwise means leads to a surprisingly high efficiency across many distributions of practical interest. The properties of P n are presented under a unified generalised L-statistics framework, which encompasses numerous other scale estimators. Extensions to P n are proposed, including taking the range of the middle τ×100% instead of just the middle 50% of the pairwise means as well as trimming and Winsorising both the original data and the pairwise means. Furthermore, we have implemented a method using adaptive trimming, which achieves a maximal breakdown value. We investigate the efficiency properties of the pairwise mean scale estimator relative to a number of other established robust scale estimators over a broad range of distributions using the corresponding maximum likelihood estimates as a common base for comparison.