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Diffusions of perturbed principal component analysis

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  • Bru, Marie-France
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    Abstract

    We propose a stochastic differential equation approach to principal component analysis. We give the equations governing the spectrum of the square BTB of a n-p matrix of independent Brownian motions. We apply this result to P.C.A. of perturbed continuous data.

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    Bibliographic Info

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

    Volume (Year): 29 (1989)
    Issue (Month): 1 (April)
    Pages: 127-136

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    Handle: RePEc:eee:jmvana:v:29:y:1989:i:1:p:127-136

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    Related research

    Keywords: stochastic differential equations sample covariance matrix eigenvalues principal component analysis;

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    Cited by:
    1. Mayerhofer, Eberhard & Pfaffel, Oliver & Stelzer, Robert, 2011. "On strong solutions for positive definite jump diffusions," Stochastic Processes and their Applications, Elsevier, vol. 121(9), pages 2072-2086, September.
    2. Christa Cuchiero & Damir Filipovi\'c & Eberhard Mayerhofer & Josef Teichmann, 2009. "Affine processes on positive semidefinite matrices," Papers 0910.0137, arXiv.org, revised Apr 2011.
    3. Joan Jasiak & R. Sufana & C. Gourieroux, 2005. "The Wishart Autoregressive Process of Multivariate Stochastic Volatility," Working Papers 2005_2, York University, Department of Economics.

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