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 Mardia's 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
Multivariate statistical methods often require the assumption of multivariate normality. The purpose...
The problem of testing the hypothesis of multivariate normality is discussed. Several methods of tr...
Based on Läuter's [Läuter, J., 1996. Exact t and F tests for analyzing studies with multiple endpoin...
In this article, we propose a new multiple test procedure for assessing multivariate normality, whic...
We propose a new class of rotation invariant and consistent goodness-of-fit tests for multivariate d...
AMS: 62H15 We consider the problem of testing multinormality against alternatives inva-riant with re...
We study the empirical size and power of some recently proposed tests for multivariate normality (MV...
AbstractLetX1, …, Xnbe i.i.d. randomd-vectors,d⩾1, with sample meanXand sample covariance matrixS. F...
AbstractWe propose a new class of rotation invariant and consistent goodness-of-fit tests for multiv...
Methods of assessing the degree to which multivariate data deviate from multinormality are discussed...
A Monte Carlo power study of 10 multivariate normality goodness-of-fit tests is presented. First, mu...
AbstractA Monte Carlo power study of 10 multivariate normality goodness-of-fit tests is presented. F...
Assessing the assumption of multivariate normality is required by many parametric multivariate stati...
For multivariate normal models and exponential family models a multiple testing stepwise method is o...
SIGLETIB Hannover: RN 3019(220) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische Inform...
Multivariate statistical methods often require the assumption of multivariate normality. The purpose...
The problem of testing the hypothesis of multivariate normality is discussed. Several methods of tr...
Based on Läuter's [Läuter, J., 1996. Exact t and F tests for analyzing studies with multiple endpoin...
In this article, we propose a new multiple test procedure for assessing multivariate normality, whic...
We propose a new class of rotation invariant and consistent goodness-of-fit tests for multivariate d...
AMS: 62H15 We consider the problem of testing multinormality against alternatives inva-riant with re...
We study the empirical size and power of some recently proposed tests for multivariate normality (MV...
AbstractLetX1, …, Xnbe i.i.d. randomd-vectors,d⩾1, with sample meanXand sample covariance matrixS. F...
AbstractWe propose a new class of rotation invariant and consistent goodness-of-fit tests for multiv...
Methods of assessing the degree to which multivariate data deviate from multinormality are discussed...
A Monte Carlo power study of 10 multivariate normality goodness-of-fit tests is presented. First, mu...
AbstractA Monte Carlo power study of 10 multivariate normality goodness-of-fit tests is presented. F...
Assessing the assumption of multivariate normality is required by many parametric multivariate stati...
For multivariate normal models and exponential family models a multiple testing stepwise method is o...
SIGLETIB Hannover: RN 3019(220) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische Inform...
Multivariate statistical methods often require the assumption of multivariate normality. The purpose...
The problem of testing the hypothesis of multivariate normality is discussed. Several methods of tr...
Based on Läuter's [Läuter, J., 1996. Exact t and F tests for analyzing studies with multiple endpoin...