Robust analogs to the coefficient of variation
Robust analogs to the coefficient of variation
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DOI：
10.1080/02664763.2020.1808599
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发表时间：
2020-08-21
影响因子：
1.5
通讯作者：
Staudte, Robert G.
中科院分区：
文献类型：
--
作者：
Arachchige, Chandima N. P. G.;Prendergast, Luke A.;Staudte, Robert G.
变异系数（CV）通常用于测量相对分散度。然而，由于它是基于样本均值和标准差，离群值可能会对其产生不利影响。此外，对于偏态分布，均值和标准差可能难以解释，因此，也可能是这种情况。在这里，我们调查的程度，基于分位数的措施，相对分散可以提供适当的总结信息作为替代CV。特别是，我们调查两个措施，第一个是四分位数范围（代替标准差），除以中位数（代替平均值），第二个是中位数绝对偏差，除以中位数，作为相对分散的稳健估计。除了比较竞争估计的影响函数及其渐近偏差和方差，我们比较区间估计使用模拟研究，以评估覆盖。
The coefficient of variation(CV)is commonly used to measure relative dispersion. However, since it is based on the sample mean and standard deviation, outliers can adversely affect it. Additionally, for skewed distributions the mean and standard deviation may be difficult to interpret and, consequently, that may also be the case for the. Here we investigate the extent to which quantile-based measures of relative dispersion can provide appropriate summary information as an alternative to the CV. In particular, we investigate two measures, the first being the interquartile range (in lieu of the standard deviation), divided by the median (in lieu of the mean), and the second being the median absolute deviation, divided by the median, as robust estimators of relative dispersion. In addition to comparing the influence functions of the competing estimators and their asymptotic biases and variances, we compare interval estimators using simulation studies to assess coverage.