Multiblock and hierarchical PCA and PLS methods have been proposed in the recent literature in order to improve the interpretability of multivariate models. They have been used in cases where the number of variables is large and additional information is available for blocking the variables into con
Application of Multiblock and Hierarchical PCA and PLS Models for Analysis of AC Voltammetric Data
β Scribed by Aleksander Jaworski; Kazimierz Wikiel; Hanna Wikiel
- Publisher
- John Wiley and Sons
- Year
- 2005
- Tongue
- English
- Weight
- 153 KB
- Volume
- 17
- Category
- Article
- ISSN
- 1040-0397
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β¦ Synopsis
Abstract
Several multiblock and hierarchical calibration techniques have been applied to the determination of the brightener concentration in industrial copper electroplating baths. Hierarchical Principal Component Regression (HPCR), Hierarchical Partial Least Squares (HPLS), Consensus PCR (CPCR), and Multiblock PLS (MBPLS) were used to build and test calibration models based on AC voltammetric data. All of the hierarchical and multiblock techniques employed produce a reliable calibration model and provide information about its robustness.
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