首页|Multivariate normality test based on kurtosis with two-step monotone missing data
Multivariate normality test based on kurtosis with two-step monotone missing data
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NSTL
Elsevier
This paper deals with a sample measure of multivariate kurtosis, which is used as a test statistic in multivariate normality testing problems. We define a new multivariate sample kurtosis measure to provide a multivariate normality test for data with a twostep monotone missing structure. Furthermore, we derive its expectation and variance using a perturbation method. To evaluate the accuracy of a normal approximation, we conducted a Monte Carlo simulation for certain parameters. Finally, we present a numerical example to illustrate the proposed procedure. (c) 2021 Elsevier Inc. All rights reserved.
Asymptotic expansionMomentMonte Carlo simulationMultivariate kurtosisNormal approximationMAXIMUM-LIKELIHOOD-ESTIMATIONCOVARIANCE-MATRIXMEAN VECTORSKEWNESS
NSTL
Elsevier
