title: A consensus successive projections algorithm--multiple linear regression method for analyzing near infrared spectra.
abstract: The successive projections algorithm (SPA) is widely used to select variables for multiple linear regression (MLR) modeling. However, SPA used only once may not obtain all the useful information of the full spectra, because the number of selected variables cannot exceed the number of calibration samples in the SPA algorithm. Therefore, the SPA-MLR method risks the loss of useful information. To make a full use of the useful information in the spectra, a new method named "consensus SPA-MLR" (C-SPA-MLR) is proposed herein. This method is the combination of consensus strategy and SPA-MLR method. In the C-SPA-MLR method, SPA-MLR is used to construct member models with different subsets of variables, which are selected from the remaining variables iteratively. A consensus prediction is obtained by combining the predictions of the member models. The proposed method is evaluated by analyzing the near infrared (NIR) spectra of corn and diesel. The results of C-SPA-MLR method showed a better prediction performance compared with the SPA-MLR and full-spectra PLS methods. Moreover, these results could serve as a reference for combination the consensus strategy and other variable selection methods when analyzing NIR spectra and other spectroscopic techniques.
authors.affiliation: College of Physics and Electronic Engineering Information, Wenzhou University, Chashan University Town, Wenzhou, Zhejiang Province, People's Republic of China.
authors.forename: Ke
authors.initials: K
authors.lastname: Liu
authors.affiliation: College of Physics and Electronic Engineering Information, Wenzhou University, Chashan University Town, Wenzhou, Zhejiang Province, People's Republic of China. Electronic address: chenxj@wzu.edu.cn.
authors.forename: Xiaojing
authors.initials: X
authors.lastname: Chen
authors.affiliation: College of Physics and Electronic Engineering Information, Wenzhou University, Chashan University Town, Wenzhou, Zhejiang Province, People's Republic of China.
authors.forename: Limin
authors.initials: L
authors.lastname: Li
authors.affiliation: College of Physics and Electronic Engineering Information, Wenzhou University, Chashan University Town, Wenzhou, Zhejiang Province, People's Republic of China.
authors.forename: Huiling
authors.initials: H
authors.lastname: Chen
authors.affiliation: College of Physics and Electronic Engineering Information, Wenzhou University, Chashan University Town, Wenzhou, Zhejiang Province, People's Republic of China.
authors.forename: Xiukai
authors.initials: X
authors.lastname: Ruan
authors.affiliation: College of Physics and Electronic Engineering Information, Wenzhou University, Chashan University Town, Wenzhou, Zhejiang Province, People's Republic of China.
authors.forename: Wenbin
authors.initials: W
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D066264:Datasets as Topic; D005742:Gasoline / Q000032:analysis; D016014:Linear Models; D012984:Software; D019265:Spectroscopy, Near-Infrared / Q000379:methods* / Q000706:statistics & numerical data; D003313:Zea mays / Q000737:chemistry
chemical_list: D005742:Gasoline
keywords: Consensus model; Multiple linear regression; Near infrared spectra; Successive projections algorithm; Variable selection