Variable selection in principal component analysis

Yuichi Mori, Masaya Iizuka, Tomoyuki Tarumi, Yutaka Tanaka

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationStatistical Methods for Biostatistics and Related Fields
PublisherSpringer Berlin Heidelberg
Number of pages19
ISBN (Print)9783540326908
Publication statusPublished - Dec 1 2007
Externally publishedYes

ASJC Scopus subject areas

  • Mathematics(all)


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