DYNAMIC MDS METHODS FOR THREE-WAY ASYMMETRIC DISSIMILARITY DATA

Classification of three-way data by the dissimilarity representation

Representation of objects by multi-dimensional data arrays has become very common for many research areas e.g. image analysis, signal processing and chemometrics. In most cases, it is the straightforward representation obtained from sophisticated measurement equipments e.g. radar signal processing. Although the use of this complex data structure could be advantageous for a better discrimination...

Structural Classification Analysis of Three-Way Dissimilarity Data

The paper presents a methodology for classifying three-way dissimilarity data, which are reconstructed by a small number of consensus classifications of the objects each defined by a sum of two order constrained distance matrices, so as to identify both a partition and an indexed hierarchy. Specifically, the dissimilarity matrices are partitioned in homogeneous classes and, within each class, a...

Reconstructing One-Mode Three-way Asymmetric Data for Multidimensional Scaling

Some models have been proposed to analyze one-mode three-way data [e.g. De Rooij and Gower (J Classification 20:181–220, 2003), De Rooij and Heiser (Br J Math Stat Psychol 53:99–119, 2000)]. These models usually assume triadic symmetric relationships. Therefore, it is general to transform asymmetric data into symmetric proximity data when one-mode three-way asymmetric proximity data are analyze...

The Dissimilarity Representation as a Tool for Three-Way Data Classification: A 2D Measure

The dissimilarity representation has demonstrated advantages in the solution of classification problems. Meanwhile, the representation of objects by multi-dimensional arrays is necessary in many research areas. However, the development of proper classification tools that take the multi-way structure into account is incipient. This paper introduces the use of the dissimilarity representation as ...

Dynamic Analysis of Three Dimensional Asymmetric Isolated Structures