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¦
An approach to interval estimation in partial least squares regression
β Scribed by A. Phatak; P.M. Reilly; A. Penlidis
- Book ID
- 118308701
- Publisher
- Elsevier Science
- Year
- 1993
- Tongue
- English
- Weight
- 601 KB
- Volume
- 277
- Category
- Article
- ISSN
- 0003-2670
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