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Behaviormetrika
Article . 1989 . Peer-reviewed
License: Springer TDM
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Sensitivity Analysis in Multidimensional Scaling

Authors: Ueda, Tohru;

Sensitivity Analysis in Multidimensional Scaling

Abstract

A sensitivity analysis method for eigenvalue problems in multivariate analysis was proposed by De Sarbo, et al. (1982) and developed by Ueda (1988). Metric multidimensional scaling (MDS) is a spectral decomposition of symmetric matrices, where eigenvalues and eigenvectors play important roles. It is shown that the e -neighborhood vectors defined in Ueda (1988) give the 2e-neighborhood vectors for the goodness-of-fit index in a spectral decomposition. Considering this fact and using the same method as Ueda (1988), sensitivity for metric MDS is discussed.

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Keywords

multidimensional scaling, sensitivity analysis, eigenvalue problem, Young-Householder transformation, ε-neighborhood

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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