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An Omnibus Test for Univariate and Multivariate Normality

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  • Jurgen A. Doornik
  • Henrik Hansen

Abstract

We suggest a convenient version of the omnibus test for normality, using skewness and kurtosis based on Shenton and Bowman [Journal of the American Statistical Association (1977) Vol. 72, pp. 206–211], which controls well for size, for samples as low as 10 observations. A multivariate version is introduced. Size and power are investigated in comparison with four other tests for multivariate normality. The first power experiments consider the whole skewness–kurtosis plane; the second use a bivariate distribution which has normal marginals. It is concluded that the proposed test has the best size and power properties of the tests considered.

Suggested Citation

  • Jurgen A. Doornik & Henrik Hansen, 2008. "An Omnibus Test for Univariate and Multivariate Normality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 927-939, December.
  • Handle: RePEc:bla:obuest:v:70:y:2008:i:s1:p:927-939
    DOI: 10.1111/j.1468-0084.2008.00537.x
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    1. Srivastava, M. S. & Hui, T. K., 1987. "On assessing multivariate normality based on shapiro-wilk W statistic," Statistics & Probability Letters, Elsevier, vol. 5(1), pages 15-18, January.
    2. Jean-Marie Dufour & Abdeljelil Farhat & Lucien Gardiol & Lynda Khalaf, 1998. "Simulation-based finite sample normality tests in linear regressions," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages 154-173.
    3. Srivastava, M. S., 1984. "A measure of skewness and kurtosis and a graphical method for assessing multivariate normality," Statistics & Probability Letters, Elsevier, vol. 2(5), pages 263-267, October.
    4. Bera, A. & John, S., 1983. "Tests for multivariate normality with Pearson alternatives," LIDAM Reprints CORE 534, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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