Canonical transformations of skew-normal variates

被引：0
作者：
Nicola Loperfido
机构：
[1] Università di Urbino “Carlo Bo”,Facoltà di Economia
来源：
TEST | 2010年 / 19卷
关键词：
Independent component analysis; Normalizing transformations; Principal components analysis; Skewness; Kurtosis; 62F03; 62E17; 62P25;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Conditions are given for linear functions of skew-normal random vectors to maximize skewness and kurtosis. As a direct implication, several measures of their multivariate skewness and kurtosis are shown to be equivalent. An estimator of the shape parameter with good statistical properties is also considered. These results are strictly related to canonical forms of skew-normal distributions and linear transformations to normality.
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页码：146 / 165
页数：19
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