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Principal Component Analysis of Large Dispersion Matrices

C. R. Narayanaswamy and D. Raghavarao
Journal of the Royal Statistical Society. Series C (Applied Statistics)
Vol. 40, No. 2 (1991), pp. 309-316
Published by: Wiley for the Royal Statistical Society
DOI: 10.2307/2347595
Stable URL: http://www.jstor.org/stable/2347595
Page Count: 8
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Principal Component Analysis of Large Dispersion Matrices
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Abstract

Sometimes it may be necessary to find the first few dominant principal components of a dispersion (covariance) matrix of large order. For many computers such problems could be too big to handle. This paper provides an effective approach to such situations through a series of splitting and merging operations on subsets of variables. An illustration is provided with applications of the suggested technique to stock price data.

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