Bias-reduced estimates for skewness, kurtosis, L-skewness and L-kurtosis

被引:10
|
作者
Withers, Christopher S. [2 ]
Nadarajah, Saralees [1 ]
机构
[1] Univ Manchester, Sch Math, Manchester M13 9PL, Lancs, England
[2] Ind Res Ltd, Appl Math Grp, Lower Hutt, New Zealand
关键词
Bias; Kurtosis; L-moments; Maximum; Nonparametric; Skewness; LOCALLY WEIGHTED REGRESSION; L-MOMENTS; SMOOTHING SCATTERPLOTS; ORDER-STATISTICS; DISTRIBUTIONS;
D O I
10.1016/j.jspi.2011.06.024
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Estimates based on L-moments are less non-robust than estimates based on ordinary moments because the former are linear combinations of order statistics for all orders, whereas the later take increasing powers of deviations from the mean as the order increases. Estimates based on L-moments can also be more efficient than maximum likelihood estimates. Similarly, L-skewness and L-kurtosis are less non-robust and more informative than the traditional measures of skewness and kurtosis. Here, we give nonparametric bias-reduced estimates of both types of skewness and kurtosis. Their asymptotic computational efficiency is infinitely better than that of corresponding bootstrapped estimates. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:3839 / 3861
页数:23
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