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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Variable Selection in Principal Component Analysis
verfasst von : Yuichi Mori, Masaya Iizuka, Tomoyuki Tarumi, Yutaka Tanaka
Erschienen in: Statistical Methods for Biostatistics and Related Fields
Verlag: Springer Berlin Heidelberg
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While there exist several criteria by which to select a reasonable subset of variables in the context of PCA, we introduce herein variable selection using criteria in
Tanaka and Mori (1997)’s
modified PCA (M.PCA) among others.
In order to perform such variable selection via XploRe, the quantlib vaspca, which reads all the necessary quantlets for selection, is first called, and then the quantlet mpca is run using a number of selection parameters.
In the first four sections we present brief explanations of variable selection in PCA, an outline of M.PCA and flows of four selection procedures, based mainly on
Tanaka and Mori (1997)’s
,
Mori (1997)
,
Mori, Tarumi and Tanaka (1998)
and
Iizuka et al. (2002a)
. In the last two sections, we illustrate the quantlet mpca and its performance by two numerical examples.