Least squares algorithms for constructing constrained ultrametric and additive tree representations of symmetric proximity data

Author:

De Soete Geert,Carroll J. Douglas,DeSarbo Wayne S.

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Psychology (miscellaneous),Mathematics (miscellaneous)

Reference33 articles.

1. CARROLL, J.D., CLARK, L. A., and DeSARBO, W. S. (1984). “The Representation of Three-way Proximity Data by Single and Multiple Tree Structure Models,”Journal of Classification, 1, 25–74.

2. CARROLL, J. D., and PRUZANSKY, S. (1975). “Fitting of Hierarchical Tree Structure (HTS) Models, Mixtures of HTS Models, and Hybrid Models, via Mathematical Programming and Alternating Least Squares,” Paper presented at the U.S.-Japan Seminar on Theory, Methods, and Applications of Multidimensional Scaling and Related Techniques, San Diego, CA.

3. CARROLL, J. D., and PRUZANSKY, S. (1980), “Discrete and Hybrid Scaling Models,” inSimilarity and Choice, eds. E. D. Lantermann and H. Feger, Bern: Huber, 108–139.

4. CHANDON, J. L. and De SOETE, G. (1984), “Fitting a Least Squares Ultrametric to Dissimilarity Data: Approximation versus Optimization,” inData Analysis and Informatics III, eds., E. Diday, M. Jambu, L. Lebart, J. Pages, and R. Tomassone, Amsterdam: North-Holland, 213–221.

5. CHANDON, J.L., LEMAIRE, J., and POUGET, J. (1980), “Construction de l'ultramétrique la plus proche d'une dissimilarité au sens des moindres carrés”,R.A.I.R.O. Recherche Opérationelle, 14, 157–170.

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