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Testing the Equality of Mean Vectors for Paired Doubly Multivariate Observations

Author

Listed:
  • Anuradha Roy

    (UTSA)

  • Ricardo Leiva

Abstract

In this article we develop a new test statistic for testing the equality of mean vectors for paired doubly multivariate observations for q response variables and u sites in blocked compound symmetric covariance matrix setting. The new testing is implemented with two real data sets.

Suggested Citation

  • Anuradha Roy & Ricardo Leiva, 2013. "Testing the Equality of Mean Vectors for Paired Doubly Multivariate Observations," Working Papers 0180mss, College of Business, University of Texas at San Antonio.
    • Handle: RePEc:tsa:wpaper:0180mss
    as

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    File URL: http://interim.business.utsa.edu/wps/mss/0017MSS-253-2013.pdf
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    References listed on IDEAS

    as
    1. Leiva, Ricardo, 2007. "Linear discrimination with equicorrelated training vectors," Journal of Multivariate Analysis, Elsevier, vol. 98(2), pages 384-409, February.
    2. 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.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Amitrajeet A. Batabyal & Hamid Beladi, 2015. "Optimal Transport Provision To A Tourist Destination: A Mechanism Design Approach," Working Papers 0140eco, College of Business, University of Texas at San Antonio.

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    More about this item

    Keywords

    Blocked compound symmetry; Paired doubly multivariate data; a natural extension of the Hotelling’s T2 statistic;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

    Statistics

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