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Location-invariant Multi-sample U-tests for Covariance Matrices with Large Dimension

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  • M. Rauf Ahmad

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  • M. Rauf Ahmad, 2017. "Location-invariant Multi-sample U-tests for Covariance Matrices with Large Dimension," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(2), pages 500-523, June.
    • Handle: RePEc:bla:scjsta:v:44:y:2017:i:2:p:500-523
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    File URL: http://hdl.handle.net/10.1111/sjos.12262
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    References listed on IDEAS

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    1. P. Harris, 1984. "An alternative test for multisample sphericity," Psychometrika, Springer;The Psychometric Society, vol. 49(2), pages 273-275, June.
    2. Chen, Song Xi & Zhang, Li-Xin & Zhong, Ping-Shou, 2010. "Tests for High-Dimensional Covariance Matrices," Journal of the American Statistical Association, American Statistical Association, vol. 105(490), pages 810-819.
    3. Jorge Mendoza, 1980. "A significance test for multisample sphericity," Psychometrika, Springer;The Psychometric Society, vol. 45(4), pages 495-498, December.
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    Cited by:

    1. Ahmad, Rauf, 2022. "Tests for proportionality of matrices with large dimension," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    2. Ahmad, M. Rauf & Ahmed, S. Ejaz, 2021. "On the distribution of the T2 statistic, used in statistical process monitoring, for high-dimensional data," Statistics & Probability Letters, Elsevier, vol. 168(C).
    3. Rauf Ahmad, M. & Pavlenko, Tatjana, 2018. "A U-classifier for high-dimensional data under non-normality," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 269-283.
    4. Rauf Ahmad, M., 2019. "A significance test of the RV coefficient in high dimensions," Computational Statistics & Data Analysis, Elsevier, vol. 131(C), pages 116-130.

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