Subjective principal component analysis
type: Item
instance of: scholarly article
title: Subjective principal component analysis
zbMATH Open document ID: 0555.62053
DOI: 10.1016/0167-9473(84)90016-1
author: Pekka J. Korhonen
published in: Computational Statistics and Data Analysis
publication date: 1984-01-01T00:00:00Z
review text: In this study we deal with the problem of finding subjective principal components for a given set of variables in a data matrix. The principal components are not determined by maximizing their variances; they are specified by a user, who can maximize the absolute values of the correlations between principal components and the variables important to him. The correlation matrix of the variables is the basic information needed in the analysis. The problem is formulated as a multiple criteria problem and solved by using an interactive procedure. The procedure is convenient to use and easy to implement. We have implemented an experimental version on an APPLE III microcomputer. A graphical display is used as an aid in finding the principal components. An illustrative application is presented, too.
Mathematics Subject Classification ID: 62H25
Mathematics Subject Classification ID: 65C99
zbMATH DE Number: 3885141
zbMATH Keywords: multicriteria optimization
zbMATH Keywords: visual
zbMATH Keywords: subjective principal components
zbMATH Keywords: correlation matrix
zbMATH Keywords: interactive procedure
MaRDI profile type: Publication
full work available at URL: 0167-9473(84)90016-1
OpenAlex ID: W2063437338
cites work: Q3894785
cites work: A hierarchical interactive method for ranking alternatives with multiple qualitative criteria
cites work: A visual interactive method for solving the multiple criteria problem
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cites work: Linear Statistical Inference and its Applications
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description: scientific article; zbMATH DE number 3885141