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Analyzing Mean Profiles of Nonnormal Populations

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  • Solomon W. Harrar
  • Jin Xu

Abstract

We consider testing whether the mean vectors of two or more populations have parallel, coincident, or flat profiles when the validity of normality is not known, and the sample sizes are moderate. Using some properties of multivariate moments and matrix manipulations, we obtain the asymptotic expansions for the null distribution of the Lawley–Hotelling statistics. We also derive the corresponding results in the situation where interest lies in coincidence and flatness alone. Accuracy of all the asymptotic expansions in approximating the exact null distributions is examined via simulation. Profile analysis of SO4 concentrations from a forestry experiment is used to illustrate the methods.

Suggested Citation

  • Solomon W. Harrar & Jin Xu, 2014. "Analyzing Mean Profiles of Nonnormal Populations," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(17), pages 3553-3573, September.
    • Handle: RePEc:taf:lstaxx:v:43:y:2014:i:17:p:3553-3573
    DOI: 10.1080/03610926.2012.697970
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    Cited by:

    1. Harrar, Solomon W. & Kong, Xiaoli, 2016. "High-dimensional multivariate repeated measures analysis with unequal covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 1-21.

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