Influence properties of trilinear partial least squares regression
β Scribed by Sven Serneels; Paul Geladi; Maarten Moens; Frank Blockhuys; Pierre J. Van Espen
- Publisher
- John Wiley and Sons
- Year
- 2005
- Tongue
- English
- Weight
- 128 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0886-9383
- DOI
- 10.1002/cem.928
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
A simple objective function in terms of undeflated X is derived for the latent variables of multivariate PLS regression. The objective function fits into the basic framework put forward by Burnham et al. (J. Chemometrics, 10, 31-45 (1996)). We show that PLS and SIMPLS differ in the constraint put on
This paper presents a formal framework for deriving partial least squares algorithms from statistical hypothesis testing. This new formulation, significance regression (SR), leads to partial least squares for scalar output problems (PLS1), to a close approximation of a common multivariable partial l