Different methods of cross-validation are studied for their suitability to guide variable-
selection algorithms to yield highly predictive models. It is shown that the commonly applied …

Hyperspectral data (Table 1) is acquired as continuous narrowbands (eg, each band with 1
to 10 nanometer or nm bandwidths) over a range of electromagnetic spectrum (eg, 400 …

In order to on-line control the quality of industrial products, often spectroscopic methods are
used in combination with regression tools. Partial Least Squares (PLS) is the most used …

Regression of a scalar response on signal predictors, such as near-infrared (NIR) spectra of
chemical samples, presents a major challenge when, as is typically the case, the dimension …

Six popular approaches of «NIR spectrum–property» calibration model building are
compared in this work on the basis of a gasoline spectral data. These approaches are …

Two of the most widely employed multivariate calibration methods, principal components
regression (PCR) and partial least squares regression (PLS), are compared using …

This paper proposes the use of least-squares support vector machines (LS-SVMs) as a
relatively new nonlinear multivariate calibration method, capable of dealing with ill-posed …

Numerous methods of multivariate calibration methods exist with ridge regression, principal
component regression, and partial least squares being the most popular methods in …

In linear regression with functional predictors and scalar responses, it may be
advantageous, particularly if the function is thought to contain features at many scales, to …

Near-infrared (NIR) spectroscopy dates back to the early 1800s when Fredrick William
Herschel, a professional musician and astronomer, discovered the first nonvisible region in …