论文标题
一类新的偏斜椭圆形分布
A new robust class of skew elliptical distributions
论文作者
论文摘要
引入了新的强大多元偏斜分布类。讨论了拟议类的参数估计方法之类的实际方面，我们表明拟议类可以在合理的时间范围内安装。我们的研究表明，分布等级能够对多元偏度结构进行建模，并且不会像其他相似复杂性的分布一样严重地受到维数的诅咒，例如规范偏斜分布类别。我们还得出了提议类的嵌套形式，该类别似乎是具有闭合形式密度函数的文献中最灵活的多元偏斜分布类。两个数据集的数值示例，i）一个数据集，其中包含英国记录的每日河流流量数据；和ii）证明了澳大利亚体育研究所（AIS）收集的运动员生物医学变量的数据集。这些示例进一步支持了中等维数据集的拟议类的实用性。
A new robust class of multivariate skew distributions is introduced. Practical aspects such as parameter estimation method of the proposed class are discussed, we show that the proposed class can be fitted under a reasonable time frame. Our study shows that the class of distributions is capable to model multivariate skewness structure and does not suffer from the curse of dimensionality as heavily as other distributions of similar complexity do, such as the class of canonical skew distributions. We also derive a nested form of the proposed class which appears to be the most flexible class of multivariate skew distributions in literature that has a closed-form density function. Numerical examples on two data sets, i) a data set containing daily river flow data recorded in the UK; and ii) a data set containing biomedical variables of athletes collected by the Australian Institute of Sports (AIS), are demonstrated. These examples further support the practicality of the proposed class on moderate dimensional data sets.
