Result: A non-linear nested partial least-squares algorithm
Title:
A non-linear nested partial least-squares algorithm
Authors:
Source:
Partial least squaresComputational statistics & data analysis. 48(1):87-101
Publisher Information:
Amsterdam: Elsevier Science, 2005.
Publication Year:
2005
Physical Description:
print, 10 ref
Original Material:
INIST-CNRS
Subject Terms:
Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Probabilités et statistiques, Probability and statistics, Statistiques, Statistics, Analyse multivariable, Multivariate analysis, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Probabilités et statistiques numériques, Numerical methods in probability and statistics, Analyse donnée, Data analysis, Análisis datos, Calcul statistique, Statistical computation, Cálculo estadístico, Estimation erreur, Error estimation, Estimación error, Modèle variable latente, Latent variable model, Modelo variable latente, Méthode moindre carré, Least squares method, Método cuadrado menor, Système non linéaire, Non linear system, Sistema no lineal, 14C20, 65F05, Algorithme PLS, PLS algorithm
Document Type:
Conference
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Centre for Process Analytics and Control Technology, School of Chemical Engineering and Advanced Materials, University of Newcastle, Merz Court, Newcastle upon Tyne NE1 7RU, United Kingdom
ISSN:
0167-9473
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.16461608
Database:
PASCAL Archive
Further Information
A nested partial least-squares (PLS) algorithm is proposed for the modelling of non-linear systems in the presence of multicollinearity. The nested algorithm comprises both an inner and outer PLS algorithm. The objective of the outer algorithm is to extract those latent variables that will form the basis of the final application whilst the role of the inner algorithm is to derive the weight vectors for the outer PLS algorithm. Wold's non-linear PLS algorithm and the error-based weight updating procedure are special cases. The nested PLS algorithm is illustrated by application to simulated data and an industrial NIR spectral data set.