Result: Discrimination on latent components with respect to patterns. Application to multicollinear data
Title:
Discrimination on latent components with respect to patterns. Application to multicollinear data
Source:
Partial least squaresComputational statistics & data analysis. 48(1):139-147
Publisher Information:
Amsterdam: Elsevier Science, 2005.
Publication Year:
2005
Physical Description:
print, 16 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 canonique, Canonical analysis, Análisis canónico, Analyse discriminante, Discriminant analysis, Análisis discriminante, Analyse donnée, Data analysis, Análisis datos, Calcul statistique, Statistical computation, Cálculo estadístico, Coefficient corrélation, Correlation coefficient, Coeficiente correlación, 62H20, 62H30, Algorithme PLS, PLS algorithm, Analyse Fisher, Fisher analysis
Document Type:
Conference
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
ENITIAA/INRA, SMAD, Unité de Sensométrie et de Chimiométrie, La Géraudière, B. P. 82228, 44322 Nantes, France
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.16461611
Database:
PASCAL Archive
Further Information
A new presentation of discriminant analysis is discussed. It consists in setting up patterns associated to the various groups and deriving latent variables in such a way that scores in each group are as highly clustered about their pattern as possible. When the conformity between observations and group patterns is investigated by means of the coefficient of correlation, Fisher's canonical discriminant analysis is retrieved. If the covariance is used instead of the coefficient of correlation, then a new and simple formalization of PLS discriminant analysis is achieved. The potential of the general approach is discussed and the methods of analysis are illustrated on the basis of a real data set.