Testing the Equality of Covariance Operators

Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)


In many situations, when dealing with several populations, equality of the covariance operators is assumed. In this work, we will study a hypothesis test to validate this assumption.


Gene Expression Pattern Recognition Stochastic Process Probability Theory Hypothesis Test 
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  1. 1.
    Boente, G., Fraiman, R.: Kernel-based functional principal components. Statist. Probab. Lett. 48, 335–345 (2000)MathSciNetMATHCrossRefGoogle Scholar
  2. 2.
    Dauxois, J., Pousse, A., Romain, Y.: Asymptotic theory for the principal component analysis of a vector random function: Some applications to statistical inference. J. Multivariate Anal. 12, 136–154 (1982)MathSciNetMATHCrossRefGoogle Scholar
  3. 3.
    Ferraty, F., View, P., Viguier-Pla, S.: Factor-based comparison of groups of curves. Comput. Stat. Data An. 51, 4903–4910 (2007)MATHCrossRefGoogle Scholar
  4. 4.
    Ledoit, O., Wolf, M.: Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size. Ann. Stat. 30 (4), 1081–1102 (2002)MathSciNetMATHCrossRefGoogle Scholar
  5. 5.
    Schott, J.: A test for the equality of covariance matrices when the dimension is large relative to the sample sizes. Comput. Stat. Data An. 51 (12), 6535–6542 (2007).MathSciNetMATHCrossRefGoogle Scholar
  6. 6.
    Seber, G.: Multivariate Observations. John Wiley and Sons (1984)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Graciela Boente
    • 1
  • Daniela Rodriguez
    • 1
  • Mariela Sued
    • 1
  1. 1.Universidad de Buenos Aires and CONICETBuenos AiresArgentina

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