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Tests for multivariate normality based on canonical correlations
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics.
2014 (English)In: Statistical Methods and Applications, ISSN 1618-2510, Vol. 23, no 2, 189-208 p.Article in journal (Refereed) Published
Abstract [en]

We propose new affine invariant tests for multivariate normality, based on independence characterizations of the sample moments of the normal distribution. The test statistics are obtained using canonical correlations between sets of sample moments in a way that resembles the construction of Mardia's skewness measure and generalizes the Lin-Mudholkar test for univariate normality. The tests are compared to some popular tests based on Mardia's skewness and kurtosis measures in an extensive simulation power study and are found to offer higher power against many of the alternatives.

Place, publisher, year, edition, pages
2014. Vol. 23, no 2, 189-208 p.
Keyword [en]
Goodness-of-fit, Kurtosis, Multivariate normality, Skewness, Test for normality
National Category
Probability Theory and Statistics Mathematics
URN: urn:nbn:se:uu:diva-228472DOI: 10.1007/s10260-013-0252-5ISI: 000337035800003OAI: oai:DiVA.org:uu-228472DiVA: diva2:734242
Available from: 2014-07-15 Created: 2014-07-15 Last updated: 2014-07-15Bibliographically approved

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Thulin, Måns
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