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
β¦ LIBER β¦
A twist to partial least squares regression
β Scribed by Ulf Indahl
- Publisher
- John Wiley and Sons
- Year
- 2005
- Tongue
- English
- Weight
- 457 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0886-9383
- DOI
- 10.1002/cem.904
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