Multivariate calibration with single-index signal regression
Document Type
Article
Publication Date
4-15-2009
Abstract
In general, linearity is assumed to hold in multivariate calibration, but this may not be true. Penalized signal regression can be extended with an explicit link function between linear prediction and response, in the spirit of single-index models. Like the vector of calibration coefficients, the unknown link function is being estimated by P-splines. Application to simulations and three data sets shows that if a non-linearity is present, it will be picked up by the model and prediction will be improved. © 2009 Elsevier B.V. All rights reserved.
Publication Source (Journal or Book title)
Chemometrics and Intelligent Laboratory Systems
First Page
196
Last Page
202
Recommended Citation
Eilers, P., Li, B., & Marx, B. (2009). Multivariate calibration with single-index signal regression. Chemometrics and Intelligent Laboratory Systems, 96 (2), 196-202. https://doi.org/10.1016/j.chemolab.2009.02.001