Selection of Variables to Preserve Multivariate Data Structure, Using Principal Components

A common objective in exploratory multivariate analysis is to identify a subset of the variables which conveys the main features of the whole sample. Analysis of a well-known multivariate data set shows that methods currently available for selecting variables in principal component analysis may not...

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Veröffentlicht in:	Applied Statistics 1987-01, Vol.36 (1), p.22-33
1. Verfasser:	Krzanowski, W. J.
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied statistics Approximation Data models Datasets Dimensionality Discriminant analysis Exact sciences and technology Group structure Mathematics Modeling Monte Carlo methods Monte Carlo simulation Multivariate analysis Principal component analysis Principal components analysis Probability and statistics Procrustes rotation Sciences and techniques of general use Singular value decomposition Statistics Variable selection
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