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Discarding Variables in a Principal Component Analysis. II: Real Data

I. T. Jolliffe
Journal of the Royal Statistical Society. Series C (Applied Statistics)
Vol. 22, No. 1 (1973), pp. 21-31
Published by: Wiley for the Royal Statistical Society
DOI: 10.2307/2346300
Stable URL: http://www.jstor.org/stable/2346300
Page Count: 11
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Discarding Variables in a Principal Component Analysis. II: Real Data
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Abstract

In this paper it is shown for four sets of real data, all published examples of principal component analysis, that the number of variables used can be greatly reduced with little effect on the results obtained. Five methods for discarding variables, which have previously been successfully tested on artificial data (Jolliffe, 1972), are used. The methods are compared and all are shown to be satisfactory for real, as well as artificial, data, although none is shown to be overwhelmingly superior to the others.

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