A New Bootstrap-Based Stopping Criterion in PLS Components Construction

DOI10.1007/978-3-319-40643-5_18zbMath1366.62138OpenAlexW2531259843MaRDI QIDQ5278379

Jérémy Magnanensi, Myriam Maumy-Bertrand, Frédéric Bertrand, Nicolas Meyer

Publication date: 19 July 2017

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-40643-5_18

zbMATH Keywords

bootstraprobustnesscross-validationinferencedifferent noise levelspartial least squares regressions (PLSR)

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Generalized linear models (logistic models) (62J12) Bootstrap, jackknife and other resampling methods (62F40)

Uses Software

• plsRglm

Cites Work

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• The Degrees of Freedom of Partial Least Squares Regression
• PLS generalised linear regression
• Bootstrapping regression models
• The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses

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