Multivariate statistical simulation
Multivariate statistical simulation
A comparative study of goodness-of-fit tests for multivariate normality
Journal of Multivariate Analysis
A new approach to the BHEP tests for multivariate normality
Journal of Multivariate Analysis
A new test for multivariate normality
Journal of Multivariate Analysis
A goodness-of-fit test for normality based on polynomial regression
Computational Statistics & Data Analysis
On the choice of the smoothing parameter for the BHEP goodness-of-fit test
Computational Statistics & Data Analysis
Generalized Cramér-von Mises goodness-of-fit tests for multivariate distributions
Computational Statistics & Data Analysis
A generalized Shapiro-Wilk W statistic for testing high-dimensional normality
Computational Statistics & Data Analysis
Goodness-of-fit tests based on empirical characteristic functions
Computational Statistics & Data Analysis
| Hi-index | 0.03 |
A multiple test procedure for assessing multivariate normality (MVN) is proposed. The new test combines a finite set of affine invariant test statistics for MVN through an improved Bonferroni method. The usefulness of such an approach is illustrated by a multiple test including the Mardia and BHEP (Baringhaus-Henze-Epps-Pulley) tests that are among the most recommended procedures for testing MVN. A simulation study carried out for a wide range of alternative distributions, in order to analyze the finite sample power behavior of the proposed multiple test procedure, indicates that the new test demonstrates a good overall performance against other highly recommended MVN tests.