Modern Multidimensional Scaling Theory and Applications
Multidimensional scaling (MDS) is a technique for the analysis of similarity or dissimilarity data on a set of objects. Such data may be intercorrelations of test items, ratings of similarity on political candidates, or trade indices for a set of countries. MDS attempts to model such data as distanc...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
New York, NY
Springer New York
1997, 1997
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| Edition: | 1st ed. 1997 |
| Series: | Springer Series in Statistics
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- I Fundamentals of MDS
- 1 The Four Purposes of Multidimensional Scaling
- 2 Constructing MDS Representations
- 3 MDS Models and Measures of Fit
- 4 Three Applications of MDS
- 5 MDS and Facet Theory
- 6 How to Obtain Proximities
- II MDS Models and Solving MDS Problems
- 7 Matrix Algebra for MDS
- 8 A Majorization Algorithm for Solving MDS
- 9 Metric and Nonmetric MDS
- 10 Confirmatory MDS
- 11 MDS Fit Measures, Their Relations, and Some Algorithms
- 12 Classical Scaling
- 13 Special Solutions, Degeneracies, and Local Minima
- III Unfolding
- 14 Unfolding
- 15 Special Unfolding Models
- IV MDS Geometry as a Substantive Model
- 16 MDS as a Psychological Model
- 17 Scalar Products and Euclidean Distances
- 18 Euclidean Embeddings
- V MDS and Related Methods
- 19 Procrustes Procedures
- 20 Three-Way Procrustean Models
- 21 Three-Way MDS Models
- 22 Methods Related to MDS
- VI Appendices
- A Computer Programs for MDS
- B Notation
- References
- Author Index