An Omnibus Test for Univariate and Multivariate Normality*

A new test for multivariate normality

We propose a new class of rotation invariant and consistent goodness-of-fit tests for multivariate distributions based on Euclidean distance between sample elements. The proposed test applies to any multivariate distribution with finite second moments. In this article we apply the new method for testing multivariate normality when parameters are estimated. The resulting test is affine invariant...

An affine invariant multiple test procedure for assessing multivariate normality

Amultiple test procedure for assessing multivariate normality (MVN) that combines a finite set of affine invariant test statistics for MVN is proposed. This combination is based on a method introduced by Fromont and Laurent (Ann. Statist., 680–720, 34, 2006) that can be viewed as an improvement of the classical Bonferroni’s method. The usefulness of such approach is illustrated through a multip...

Predictive factors for infertility of women: an univariate and multivariate logistic regression analysis

Background and aims: Infertility is a major problem during reproductive age. Physical and psychological effects of infertility in women are problematic. The aim of this study was to determine the potential predictive factors of infertility, among women referring both public and private health centers in Ilam province, western Iran, in 2013. Methods: In this cross-sectional study, 1013 women re...

ReductionCriterion and Multivariate Normality

An Empirical Likelihood Ratio Test for Normality

The empirical likelihood ratio (ELR) test for the problem of testing for normality is derived in this paper. The sampling properties of the ELR test and four other commonly used tests are provided and analyzed using the Monte Carlo simulation technique. The power comparisons against a wide range of alternative distributions show that the ELR test is the most powerful of these tests in certain s...