An overview of variable selection methods in multivariate analysis of near-infrared spectra

By Yong-Huan Yun, Hong-Dong Li, Bai-Chuan Deng, Dongsheng Cao. Trends in Analytical Chemistry (TrAC), 2019

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Abstract With the advances in innovative instrumentation and various valuable applications, near-infrared (NIR) spectroscopy has become a mature analytical technique in various fields. Variable (wavelength) selection is a critical step in multivariate calibration of NIR spectra, which can improve the prediction performance, make the calibration reliable and provide simpler interpretation. During the last several decades, there have been a large number of variable selection methods proposed in NIR spectroscopy. In this paper, we generalize variable selection methods in a simple manner to introduce their classifications, merits and drawbacks, to provide a better understanding of their characteristics, similarities and differences. We also introduce some hybrid and modified methods, highlighting their improvements. Finally, we summarize the limitations of existing variable selection methods, providing our remarks and suggestions on the development of variable selection methods, to promote the development of NIR spectroscopy.

Subfields: Analytical Chemistry, Biomedical Engineering, Biophysics

View Paper: https://www.semanticscholar.org/paper/455dd6ebcd9aa12e6586d34ef78c5360c2ca0f15