The Young-Householder algorithm and the least squares multidimensional scaling of squared distances
- M. W. Browne
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It is shown that replacement of the zero diagonal elements of the symmetric data matrix of approximate squared distances by certain other quantities in the Young-Householder algorithm will yield a least squares fit to squared distances instead of to scalar products. Iterative algorithms for obtaining these replacement diagonal elements are described and relationships with the ELEGANT algorithm (de Leeuw 1975; Takane 1977) are discussed. In “large residual” situations a penalty function approach, motivated by the ELEGANT algorithm, is adopted. Empirical comparisons of the algorithms are given.
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- The Young-Householder algorithm and the least squares multidimensional scaling of squared distances
Journal of Classification
Volume 4, Issue 2 , pp 175-190
- Cover Date
- Print ISSN
- Online ISSN
- Additional Links
- Classical scaling
- ELEGANT algorithm
- Squared distances
- M. W. Browne (1)
- Author Affiliations
- 1. Department of Statistics, University of South Africa, P.O. Box 392, 0001, Pretoria, South Africa