☆ 4.7 Article Proceedings Paper

Bootstrap-based (Q)over-capkh2 for the selection of components and variables in PLS regression

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2003)

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Journal

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
Volume 68, Issue 1-2, Pages 5-16

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/S0169-7439(03)00083-2

Keywords

PLSR; irrelevant factors; bootstrap; cross-validation

Categories

Automation & Control Systems Chemistry, Analytical Computer Science, Artificial Intelligence Instruments & Instrumentation Mathematics, Interdisciplinary Applications Statistics & Probability

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The aim of this paper is to suggest a bootstrap-based method for choosing the number of components in Partial Least Squares Regression (PLSR). Cross-validated Q(h)(2) statistic is used, for which is intended to derive a bootstrap distribution and to perform a hypothesis testing. Monte Carlo approximation is adopted. Applications on both artificial and real data are presented. (C) 2003 Elsevier B.V. All rights reserved.

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