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Multi-level multivariate normal distribution with self-similar compound symmetry covariance matrix

Author

Listed:
  • Ricardo Leiva
  • Anuradha Roy

    (UTSA)

Abstract

We study multi-level multivariate normal distribution with self similar compound symmetry co-variance structure for k di erent levels of the multivariate data. Both maximum likelihood and unbiased estimates of the matrix parameters are obtained. The spectral decomposition of the new covariance structure are discussed and are demonstrated with a real dataset from medical studies.

Suggested Citation

  • Ricardo Leiva & Anuradha Roy, 2016. "Multi-level multivariate normal distribution with self-similar compound symmetry covariance matrix," Working Papers 0146mss, College of Business, University of Texas at San Antonio.
    • Handle: RePEc:tsa:wpaper:0146mss
    as

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    File URL: http://interim.business.utsa.edu/wps/mss/0002MSS-253-2016.pdf
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    References listed on IDEAS

    as
    1. Anuradha Roy, 2014. "A two-stage principal component analysis of symbolic data using equicorrelated and jointly equicorrelated covariance structures," Working Papers 0164mss, College of Business, University of Texas at San Antonio.
    2. Hao, Chengcheng & Liang, Yuli & Roy, Anuradha, 2015. "Equivalency between vertices and centers-coupled-with-radii principal component analyses for interval data," Statistics & Probability Letters, Elsevier, vol. 106(C), pages 113-120.
    3. Roy, Anuradha & Leiva, Ricardo & Žežula, Ivan & Klein, Daniel, 2015. "Testing the equality of mean vectors for paired doubly multivariate observations in blocked compound symmetric covariance matrix setup," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 50-60.
    4. Leiva, Ricardo & Roy, Anuradha, 2012. "Linear discrimination for three-level multivariate data with a separable additive mean vector and a doubly exchangeable covariance structure," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1644-1661.
    5. Leiva, Ricardo, 2007. "Linear discrimination with equicorrelated training vectors," Journal of Multivariate Analysis, Elsevier, vol. 98(2), pages 384-409, February.
    6. Roy, Anuradha & Zmyślony, Roman & Fonseca, Miguel & Leiva, Ricardo, 2016. "Optimal estimation for doubly multivariate data in blocked compound symmetric covariance structure," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 81-90.
    7. Roy, Anuradha & Leiva, Ricardo, 2008. "Likelihood ratio tests for triply multivariate data with structured correlation on spatial repeated measurements," Statistics & Probability Letters, Elsevier, vol. 78(13), pages 1971-1980, September.
    8. Ohlson, Martin & Rauf Ahmad, M. & von Rosen, Dietrich, 2013. "The multilinear normal distribution: Introduction and some basic properties," Journal of Multivariate Analysis, Elsevier, vol. 113(C), pages 37-47.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Eigenblock; eigenmatrix; k??level data; self-similar compound symmetry covariance structure;
    All these keywords.

    JEL classification:

    • H12 - Public Economics - - Structure and Scope of Government - - - Crisis Management
    • H25 - Public Economics - - Taxation, Subsidies, and Revenue - - - Business Taxes and Subsidies

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