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Some Applications of Watson's Perturbation Approach to Random Matrices

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  • Ruymgaart, Frits H.
  • Yang, Song
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    Abstract

    In this note we draw attention to Watson's (1983) perturbation approach to random matrices, by which the asymptotic distribution of eigenvalues and eigenvectors can be derived in a very elegant way. We extend his result to functions of matrices and give some applications in principal component analysis, multivariate analysis, and canonical correlations.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 60 (1997)
    Issue (Month): 1 (January)
    Pages: 48-60

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    Handle: RePEc:eee:jmvana:v:60:y:1997:i:1:p:48-60

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    Related research

    Keywords: perturbations principal component analysis robustness random matrices;

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    Cited by:
    1. Cupidon, J. & Eubank, R. & Gilliam, D. & Ruymgaart, F., 2008. "Some properties of canonical correlations and variates in infinite dimensions," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1083-1104, July.
    2. Mas, André, 2002. "Weak convergence for the covariance operators of a Hilbertian linear process," Stochastic Processes and their Applications, Elsevier, vol. 99(1), pages 117-135, May.

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