More on the Supremum Statistic to Test Multivariate Skew-Normality

Computation

Timothy Opheim¹  Anuradha Roy¹ 

[1] Department of Management Science and Statistics, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA;

关键词: Monte Carlo simulations;    multivariate skewness;    skew-normal distribution;    supremum test;   

DOI  :  10.3390/computation9120126

来源: DOAJ

【 摘 要 】

This review is about verifying and generalizing the supremum test statistic developed by Balakrishnan et al. Exhaustive simulation studies are conducted for various dimensions to determine the effect, in terms of empirical size, of the supremum test statistic developed by Balakrishnan et al. to test multivariate skew-normality. Monte Carlo simulation studies indicate that the Type-I error of the supremum test can be controlled reasonably well for various dimensions for given nominal significance levels 0.05 and 0.01. Cut-off values are provided for the number of samples required to attain the nominal significance levels 0.05 and 0.01. Some new and relevant information of the supremum test statistic are reported here.

【 授权许可】

Unknown