Segmented principal component transform-partial least squares regression

被引：3

作者：

Barros, Antnio S. ^{[1
]}

Pinto, Rui

Delgadillo, Ivonne

Rutledge, Douglas N.

机构：

[1] Univ Aveiro, Dept Quim, P-3810193 Aveiro, Portugal

[2] AgroParisTech, Chim Analyt Lab, F-75005 Paris, France

来源：

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 2007年 / 89卷 / 02期

关键词：

PLS; cross validation; segmented PLS; principal component transform;

D O I：

10.1016/j.chemolab.2007.05.009

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An approach for doing PLS on very wide datasets is proposed in this work. The method is based on the decomposition, by means of a SVD, of non-superimposed segments of the original data matrix. It is shown that this approach uses less computer resources compared to SIMPLS and PCT-PLS1. Furthermore, it is also shown that the results obtained by this approach are the same as those obtained by other regression methods (PLS and SIMPLS). The method implementation is simple and can be done in a distributed environment. (c) 2007 Elsevier B.V All rights reserved.

引用

下载

页码：59 / 68

页数：10

共 50 条

[11] Functional Principal Component Regression and Functional Partial Least-squares Regression: An Overview and a Comparative Study
Febrero-Bande, Manuel
Galeano, Pedro
Gonzalez-Manteiga, Wenceslao
INTERNATIONAL STATISTICAL REVIEW, 2017, 85 (01) : 61 - 83
[12] Application of Principal Component Regression and Partial Least Squares Regression in Ultraviolet Spectrum Water Quality Detection
Li, Jiangtong
Luo, Yongdao
Dai, Honglin
2017 INTERNATIONAL CONFERENCE ON OPTICAL INSTRUMENTS AND TECHNOLOGY: OPTOELECTRONIC IMAGING/SPECTROSCOPY AND SIGNAL PROCESSING TECHNOLOGY, 2017, 10620
[13] Propagation of measurement errors for the validation of predictions obtained by principal component regression and partial least squares
Faber, Klaas
Kowalski, Bruce R.
Journal of Chemometrics, 11 (03): : 181 - 238
[14] Analysis of the impact of material properties on tabletability by principal component analysis and partial least squares regression
Mareczek, Lena
Riehl, Carolin
Harms, Meike
Reichl, Stephan
EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES, 2024, 200
[15] MULTICOMPONENT PRINCIPAL COMPONENT REGRESSION AND PARTIAL LEAST-SQUARES ANALYSES OF OVERLAPPED CHROMATOGRAPHIC PEAKS
FAIGLE, JF
POPPI, RJ
SCARMINIO, IS
BRUNS, RE
JOURNAL OF CHROMATOGRAPHY, 1991, 539 (01): : 123 - 132
[16] Propagation of measurement errors for the validation of predictions obtained by principal component regression and partial least squares
Faber, K
Kowalski, BR
JOURNAL OF CHEMOMETRICS, 1997, 11 (03) : 181 - 238
[17] Using partial least squares and principal component regression in simultaneous spectrophotometric analysis of pyrimidine bases
Khajehsharifi, Habibollah
Eskandari, Zahra
Sareban, Neda
ARABIAN JOURNAL OF CHEMISTRY, 2017, 10 : S141 - S147
[18] Comparison of principal components regression, partial least squares regression, multi-block partial least squares regression, and serial partial least squares regression algorithms for the analysis of Fe in iron ore using LIBS
Yaroshchyk, P.
Death, D. L.
Spencer, S. J.
JOURNAL OF ANALYTICAL ATOMIC SPECTROMETRY, 2012, 27 (01) : 92 - 98
[19] A Comparative Regression Analysis between Principal Component and Partial Least Squares Methods for Flight Load Calculation
Yan, Qi
Yang, Chao
Wan, Zhiqiang
APPLIED SCIENCES-BASEL, 2023, 13 (14):
[20] Mutlivariate calibration with Raman data using fast principal component regression and partial least squares methods
Estienne, F
Massart, DL
ANALYTICA CHIMICA ACTA, 2001, 450 (1-2) : 123 - 129

← 1 2 3 4 5 →