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A Note on the Use of Principal Components in Regression
Ian T. Jolliffe
Journal of the Royal Statistical Society. Series C (Applied Statistics)
Vol. 31, No. 3 (1982), pp. 300-303
Stable URL: http://www.jstor.org/stable/2348005
Page Count: 4
You can always find the topics here!Topics: Statistical variance, Linear regression, Statism, Principal components analysis, Mathematical dependent variables, Statistical discrepancies, Climate models, Misconception, Literature, Applied statistics
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The use of principal components in regression has received a lot of attention in the literature in the past few years, and the topic is now beginning to appear in textbooks. Along with the use of principal component regression there appears to have been a growth in the misconception that the principal components with small eigenvalues will very rarely be of any use in regression. The purpose of this note is to demonstrate that these components can be as important as those with large variance. This is illustrated with four examples, three of which have already appeared in the literature.
Journal of the Royal Statistical Society. Series C (Applied Statistics) © 1982 Royal Statistical Society