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A powerful test for multivariate normality

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  • Ming Zhou
  • Yongzhao Shao

Abstract

This paper investigates a new test for normality that is easy for biomedical researchers to understand and easy to implement in all dimensions. In terms of power comparison against a broad range of alternatives, the new test outperforms the best known competitors in the literature as demonstrated by simulation results. In addition, the proposed test is illustrated using data from real biomedical studies.

Suggested Citation

  • Ming Zhou & Yongzhao Shao, 2014. "A powerful test for multivariate normality," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(2), pages 351-363, February.
  • Handle: RePEc:taf:japsta:v:41:y:2014:i:2:p:351-363
    DOI: 10.1080/02664763.2013.839637
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    File URL: http://hdl.handle.net/10.1080/02664763.2013.839637
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    Cited by:

    1. Renée Fry-McKibbin & Cody Yu-Ling Hsiao & Vance L. Martin, 2017. "Joint tests of contagion with applications to financial crises," CAMA Working Papers 2017-65, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

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