The GIFI approach to non‐linear PLS modeling
Journal of ChemometricsPublished 26 April 2001
Anders Berglund, Nouna Kettaneh, Lise‐Lott Uppgård, Svante Wold, Nancy Bendwell, Dave R. Cameron
Citations36
SJR quartileQ3
SJR score0.39
SNIP0.83
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TL;DR
The potential uses and limitations of PLS regression, in combination with four variants of GIFI coding, are investigated using both simulated and empirical data sets.
Abstract
Abstract The GIFI approach to non‐linear modeling involves the transformation of quantitative variables to a set of 1/0 dummies in a similar manner to the way qualitative variables are coded. This is followed by analyzing the sets of 1/0 dummies by principal component analysis, multiple regression or, as discussed here, PLS. The patterns of the resulting coefficients indicate the nature of the non‐linearities in the data. Here the potential uses and limitations of PLS regression, in combination with four variants of GIFI coding, are investigated using both simulated and empirical data sets. Copyright © 2001 John Wiley & Sons, Ltd.
Keywords
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