岡山大学環境理工学部研究報告 ISSN 2187-6940
Published by Faculty of Environmental Science and Technology, Okayama University

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合成変数の推定を利用した項目選択とその数値的検討

森 裕一 岡山理科大学総合情報学部
笛田 薫 岡山大学 Kaken ID publons researchmap
飯塚 誠也 岡山大学 Kaken ID researchmap
発行日
2007-03-15
抄録
A variable selection method using global score estimation is proposed, which is applicable as a selection criterion in any multivariate method without external variables such as principal component analysis. This method selects a reasonable subset of variables so that the global scores, e.g. principal component scores, which are computed based on the selected variables, approximate the original global scores as well as possible in the context of the least squares. Three computational steps are proposed to estimate the scores according to how to satisfy the restriction that the estimated global scores are mutually uncorrelated. Three different examples are analyzed to demonstrate the performance and usefulness of the proposed method numerically, in which three steps are evaluated and the results obtained using four cost-saving selection procedures are compared.
キーワード
principal components
least square
orthogonalization
cost-saving selection
ISSN
1341-9099
NCID
AN10529213
NAID
JaLCDOI