COMPUTER INTENSIVE TRIALS TO DETERMINE THE NUMBER OF VARIABLES IN PCA(Multidimensional Data Analysis)

    • Mori Yuichi
    • Department of Socio-Information, Okayama University of Science
    • Tarumi Tomoyuki
    • Department of Environmental and Mathematical Sciences, Okayama University
    • Tanaka Yutaka
    • Department of Environmental and Mathematical Sciences, Okayama University

抄録

Many criteria and procedures to select a reasonable subset of variables in the context of principal component analysis have been derived, but there still exist problems to determine how many variables should be selected as well as to evaluate the performance of the selection methods. To deal with these problems, two computer intensive methods are performed: a bootstrap method which is applied to the given subsets of variables and a cross validation method which is modified for principal component analysis. The results in some numerical examples offer information and some guidance to determine the number of variables to be selected.

収録刊行物

Journal of the Japanese Society of Computational Statistics   [巻号一覧]

Journal of the Japanese Society of Computational Statistics 15(2), 337-345, 2003-06  [この号の目次]

日本計算機統計学会

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各種コード

  • NII論文ID(NAID) :
    110001235187
  • NII書誌ID(NCID) :
    AA10823693
  • 本文言語コード :
    ENG
  • 資料種別 :
    REV
  • ISSN :
    09152350
  • 収録DB :
    CJP書誌  CJP引用  NII-ELS