Kernel partial least square regression with high resistance to multiple outliers and bad leverage points on near-infrared spectral data analysis

• Main Authors: Silalahi, Divo Dharma, Midi, Habshah, Arasan, Jayanthi, Mustafa, Mohd Shafie, Caliman, Jean-Pierre
• Format: Article
• Published: MDPI AG 2021
• Online Access: http://psasir.upm.edu.my/id/eprint/93966/; https://www.mdpi.com/2073-8994/13/4/547

Multivariate statistical analysis such as partial least square regression (PLSR) is the common data processing technique used to handle high-dimensional data space on near-infrared (NIR) spectral datasets. The PLSR is useful to tackle the multicollinearity and heteroscedasticity problem that can be...