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Bootstrap-based Q̂kh2 for the selection of components and variables in PLS regression

✍ Scribed by Silvano Amato; Vincenzo Esposito Vinzi

Publisher: Elsevier Science
Year: 2003
Tongue: English
Weight: 249 KB
Volume: 68
Category: Article
ISSN: 0169-7439
DOI: 10.1016/s0169-7439(03)00083-2

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✦ Synopsis

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.

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