Author:
Mathai Arak,Provost Serge,Haubold Hans
Abstract
AbstractThe requisite theory for the study of Principal Component Analysis has already been introduced in Chap. 1, namely, the problem of optimizing a real quadratic form that is subject to a constraint. We formulate the problem with respect to a practical situation consisting of selecting the most ``relevant'' variables in a study. Principal component analysis is actually a dimension reduction technique that projects the data onto a set of orthogonal axes. Sample principal components are defined and certain associated distributional aspects are discussed.
Publisher
Springer International Publishing
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