Generalization of Quantification for PLS CorrelationGeneralization of Quantification for PLS Correlation
- Other Titles
- Generalization of Quantification for PLS Correlation
- Authors
- 이성근; 허명회
- Issue Date
- 2012
- Publisher
- 한국통계학회
- Keywords
- Partial Least Squares(PLS); generalization of quantification for PLS correlation.
- Citation
- 응용통계연구, v.25, no.1, pp.225 - 237
- Indexed
- KCI
- Journal Title
- 응용통계연구
- Volume
- 25
- Number
- 1
- Start Page
- 225
- End Page
- 237
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/109542
- ISSN
- 1225-066X
- Abstract
- This study proposes a quantification algorithm for a PLS method with several sets of variables. We called the quantification method for PLS with more than 2 sets of data a generalization. The basis of the quantification for PLS method is singular value decomposition. To derive the form of singular value decomposition in the data with more than 2 sets more easily, we used the constraint, {a^t} a+ {b^t} {b}+{c^t} {c}=3 not a ^{t} a=1, b ^{t} b=1, and c ^{t} c=1, for instance, in the case of 3 data sets. However, to prove that there is no difference, we showed it by the use of 2 data sets case because it is very complicate to prove with 3 data sets. The keys of the study are how to form the singular value decomposition and how to get the coordinates for the plots of variables and observations.
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