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Main Author: Foschi, Paolo
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.14430
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author Foschi, Paolo
author_facet Foschi, Paolo
contents The geometrical structure of PLS shrinkages is here considered. Firstly, an explicit formula for the shrinkage vector is provided. In that expression, shrinkage factors are expressed a averages of a set of basic shrinkages that depend only on the data matrix. On the other hand, the weights of that average are multilinear functions of the observed responses. That representation allows to characterise the set of possible shrinkages and identify extreme situations where the PLS estimator has an highly nonlinear behaviour. In these situations, recently proposed measures for the degrees of freedom (DoF), that directly depend on the shrinkages, fail to provide reasonable values. It is also shown that the longstanding conjecture that the DoFs of PLS always exceeds the number PLS directions does not hold.
format Preprint
id arxiv_https___arxiv_org_abs_2510_14430
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The geometry of PLS shrinkages
Foschi, Paolo
Statistics Theory
Numerical Analysis
62G05
The geometrical structure of PLS shrinkages is here considered. Firstly, an explicit formula for the shrinkage vector is provided. In that expression, shrinkage factors are expressed a averages of a set of basic shrinkages that depend only on the data matrix. On the other hand, the weights of that average are multilinear functions of the observed responses. That representation allows to characterise the set of possible shrinkages and identify extreme situations where the PLS estimator has an highly nonlinear behaviour. In these situations, recently proposed measures for the degrees of freedom (DoF), that directly depend on the shrinkages, fail to provide reasonable values. It is also shown that the longstanding conjecture that the DoFs of PLS always exceeds the number PLS directions does not hold.
title The geometry of PLS shrinkages
topic Statistics Theory
Numerical Analysis
62G05
url https://arxiv.org/abs/2510.14430