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Article Dans Une Revue Electronic Journal of Statistics Année : 2012

Non-Metric Partial Least Squares

Résumé

In this paper I review covariance-based Partial Least Squares (PLS) methods, focusing on common features of their respective algorithms and optimization criteria. I then show how these algorithms can be adjusted for use as optimal scaling tools. Three new PLS-type algorithms are proposed for the analysis of one, two or several blocks of variables: the Non-Metric NIPALS, the Non-Metric PLS Regression and the Non-Metric PLS Path Modeling, respectively. These algorithms extend the applicability of PLS methods to data measured on different measurement scales, as well as to variables linked by non-linear relationships.
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hal-03988559 , version 1 (14-02-2023)

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Giorgio Russolillo. Non-Metric Partial Least Squares. Electronic Journal of Statistics , 2012, 6, ⟨10.1214/12-EJS724⟩. ⟨hal-03988559⟩
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