This article gives a synopsis on new developments in affine invariant tests for multivariate
normality in an iid-setting, with special emphasis on asymptotic properties of several classes …

The testing of multivariate normality remains a significant scientific problem. Although it is
being extensively researched, it is still unclear how to choose the best test based on the …

Abstract Let X 1, X 2,… be independent and identically distributed random elements taking
values in a separable Hilbert space ℍ. With applications for functional data in mind, ℍ may …

We generalize a recent class of tests for univariate normality that are based on the empirical
moment generating function to the multivariate setting, thus obtaining a class of affine …

We study a novel class of affine‐invariant and consistent tests for multivariate normality. The
tests are based on a characterization of the standard d‐variate normal distribution by way of …

The assumption of normality has underlain much of the development of statistics, including
spatial statistics, and many tests have been proposed. In this work, we focus on the …

We propose a Bayesian test of normality for univariate or multivariate data against
alternative nonparametric models characterized by Dirichlet process mixture distributions …

We study a novel class of affine invariant and consistent tests for normality in any dimension
in an iid‐setting. The tests are based on a characterization of the standard d‐variate normal …

Wind energy can be utilized for the generation of electricity, due to significant wind potential
at different parts of the world, some countries have already been generating of electricity …

Based on a chi square transform of the multivariate normal data set, we proposed a
technique for testing multinormality which is the sum of interpoint squared distances …