Advances in Data Analysis and Classification

, Volume 3, Issue 2, pp 169–184 | Cite as

On Robinsonian dissimilarities, the consecutive ones property and latent variable models

  • Matthijs J. WarrensEmail author
Open Access
Regular Article


A dissimilarity measure on a set of objects is Robinsonian if its matrix can be symmetrically permuted so that its elements do not decrease when moving away from the main diagonal along any row or column. The Robinson property of a dissimilarity reflects an order of the objects. If a dissimilarity is not observed directly, it must be obtained from the data. Given that an ordinal structure is assumed to underlie the data, the dissimilarity function of choice may or may not recover the order correctly. For four dissimilarity measures for binary data it is investigated what ordinal data structure of 0s and 1s is correctly recovered. We derive sufficient conditions for the dissimilarity functions to be Robinsonian. The sufficient conditions differ with the dissimilarity measures. The paper concludes with some limitations of the study.


Dissimilarity measures Binary data Ordinal comparison Pyramids Ordered clustering systems Weakly pseudo-hierarchies 

Mathematics Subject Classification (2000)

62H05 62H20 



The author would like to thank Hans-Hermann Bock, Maurizio Vichi and two anonymous reviewers for their helpful comments and valuable suggestions on earlier versions of this article.

Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.


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Copyright information

© The Author(s) 2009

Authors and Affiliations

  1. 1.Unit Methodology and Statistics, Institute of PsychologyLeiden UniversityLeidenThe Netherlands

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