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Trimmed and winsorized standard deviations based on a scaled deviation

机译:根据比例偏差对标准偏差进行修正和修正

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Trimmed (and winsorized) standard deviations based on a scaled deviation are introduced and studied. The influence functions and limiting distributions are obtained. The performance of the estimators with respect to high breakdown scale estimators is evaluated and compared. Unlike other high breakdown estimators which perform poorly for light-tailed distribution and when points near the centre are contaminated, the resulting trimmed (and winsorized) standard deviations are much more efficient than their predecessors at light-tailed distributions by suitably choosing the cutting parameter and highly efficient for heavy-tailed and skewed distributions. At the same time, they share the best breakdown point robustness of the sample median absolute deviation for any common trimming thresholds. Compared with their predecessors, they can achieve the best efficiency when the contaminating points are presented from areas around the centre. Indeed, the scaled-deviation-trimmed (winsorized) standard deviations behave very well overall and, consequently, represent very favourable alternatives to existing scale estimators.
机译:引入并研究了基于比例偏差的修剪(和Winsorized)标准偏差。获得影响函数和极限分布。评估并比较估计器相对于高细分规模估计器的性能。与其他在轻尾分布中表现不佳且中心附近的点受到污染的高击穿估计器不同,通过适当选择切割参数和对于重尾和偏斜的分布非常高效。同时,对于任何常见的修整阈值,它们共享样本中值绝对偏差的最佳击穿点鲁棒性。与他们的前任相比,当从中心周围的区域展示污染点时,它们可以实现最佳效率。的确,按比例偏差校正的(标准差)标准偏差在总体上表现很好,因此,它是现有比例估计器的非常好选择。

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