论文标题
基于中心向外间距的拟合测试的一些优点
Some Goodness of Fit Tests based on Centre Outward Spacings
论文作者
论文摘要
数据深度为多元数据提供了中间的顺序。最近，Li（2018）研究了一些基于数据深度的单变量GOF测试。本文讨论了基于中间间距的拟合测试的一些单变量优点。这些测试具有与通常的间距相似的渐近特性（分布和效率）。一项模拟研究表明，对于轻尾对称替代方案，提出的测试的性能比基于通常的间距的测试更好。
Data depth provides a centre-outward ordering for multivariate data. Recently, some univariate GoF tests based on data depth have been studied by Li (2018). This paper discusses some univariate goodness of fit tests based on centre-outward spacings. These tests have similar asymptotic properties (distribution and efficiency) as those based on usual spacings. A simulation study reveals that for light-tailed symmetric alternatives, the proposed tests perform better than those based on usual spacings.
