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