2014•Colloquium BiometricumRequires access

On multivariate normality tests using skewness and kurtosis

Zofia Hanusz, Joanna Tarasińska

Open publisher page 3 citations

Abstract

In the paper two new tests for multivariate normality are proposed. The tests are based on Mardia’s and Srivastava’s more accurate moments of multivariate sample skewness and kurtosis. Sample significance level and power against chosen alternative distributions of both tests were calculated via simulation studies. The obtained results have been compared to the results of two improved the Jarque-Bera’s tests and the Henze-Zirkler test

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What this paper is about

In the paper two new tests for multivariate normality are proposed. The tests are based on Mardia’s and Srivastava’s more accurate moments of multivariate sample skewness and kurtosis. Sample significance level and power against chosen alternative distributions of both tests were calculated via simulation studies. The obtained results have been compared to the results of two improved the Jarque-Bera’s tests and the Henze-Zirkler test

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In the paper two new tests for multivariate normality are proposed. The tests are based on Mardia’s and Srivastava’s more accurate moments of multivariate sample skewness and kurtosis. Sample significance level and power against chosen alternative distributions of both tests were calculated via simulation studies. The obtained results have been compared to the results of two improved the Jarque-Bera’s tests and the Henze-Zirkler test

Key concepts: Kurtosis, Normality test, Multivariate statistics, Normality, Skewness, Statistics, Mathematics, Multivariate normal distribution

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