The Representation of Three-Way Proximity Data by Single and Multiple Tree Structure Models

Journal of Classification, Volume 1, Issue 1, pp 25-74, 1984

50 Pages Posted: 11 May 2016

See all articles by J. Carroll

J. Carroll

Rutgers, The State University of New Jersey (Deceased)

Linda Clark

Bell Laboratories

Wayne S. DeSarbo

Pennsylvania State University

Date Written: December 1984

Abstract

Models for the representation of proximity data (similarities/dissimilarities) can be categorized into one of three groups of models: continuous spatial models, discrete nonspatial models, and hybrid models (which combine aspects of both spatial and discrete models). Multidimensional scaling models and associated methods, used for the spatial representation of such proximity data, have been devised to accommodate two, three, and higher-way arrays. At least one model/method for overlapping (but generally non-hierarchical) clustering called INDCLUS (Carroll and Arabic 1983) has been devised for the ease of three-way arrays of proximity data. Tree-fitting methods, used for the discrete network representation of such proximity data, have only thus far been devised to handle two-way arrays. This paper develops a new methodology called INDTREES (for individual Differences in TREE Structures) for fitting various (discrete) tree structures to three-way proximity data. This individual differences generalization is one in which different individuals, for example, are assumed to base their judgments on the same family of trees, but are allowed to have different node heights and/or branch lengths.

We initially present an introductory overview focussing on existing two-way models. The INDTREES model and algorithm are then described in detail. Monte Carlo results for the INDTREES fitting of four different three-way data sets are presented. In the application, a single ultrametric tree is fitted to three-way proximity data derived from intention-to-buy-data for various brands of over-the-counter pain relievers for relieving three common types of maladies. Finally, we briefly describe how the INDTREES procedure can be extended to accommodate hybrid modelling, as well as to handle other types of applications.

Keywords: Clustering, Alternating Least Squares, Discrete Optimization

Suggested Citation

Carroll, J. and Clark, Linda and DeSarbo, Wayne S., The Representation of Three-Way Proximity Data by Single and Multiple Tree Structure Models (December 1984). Journal of Classification, Volume 1, Issue 1, pp 25-74, 1984, Available at SSRN: https://ssrn.com/abstract=2778179

J. Carroll

Rutgers, The State University of New Jersey (Deceased)

Linda Clark

Bell Laboratories ( email )

600 Mountain Avenue
Murray Hill, NJ 07974
United States

Wayne S. DeSarbo (Contact Author)

Pennsylvania State University ( email )

University Park
State College, PA 16802
United States

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