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The structural representation of proximity matrices with MATLAB / Lawrence Hubert, Phipps Arabie, and Jacqueline Meulman.
Material type:
TextLanguage: English Publication details: Virginia : American Statistical Association, 2006.Edition: 1st edDescription: xvi, 214 p. 25.5 cmISBN: - 9780898716078
- 512.9 HUB
Contents:
Summary: This book by Lawrence Hubert, with contributions from Phipps Arabie and Jacqueline Meulman, serves as a practical guide to representing proximity data using MATLAB. It expertly demonstrates M-files for various structural representations of one-mode (symmetric) and two-mode (rectangular) proximity matrices, techniques primarily developed in behavioral sciences but now relevant in fields like bioinformatics and chemometrics. Divided into three parts, the book covers linear and circular scaling with city-block metrics, graph-theoretic tree structures (ultrametrics and additive trees), and order-based representations, particularly anti-Robinson forms, making complex analytical methods accessible through a computational approach.
1. Linear Unidimensional Scaling
2. Linear Multidimensional Scaling
3. Circular Scaling
4. LUS for Two-Mode Proximity Data
II The Representation of Proximity Matrices by Tree Structures
5. Ultrametrics for Symmetric Proximity Data
6. Additive Trees for Symmetric Proximity Data
7. Fitting Multiple Tree Structures to a Symmetric Proximity Matrix
8. Ultrametrics and Additive Trees for Two-Mode (Rectangular) Proximity Data
III The Representation of Proximity Matrices by Structures Dependent on Order (Only)
9. Anti-Robinson Matrices for Symmetric Proximity Data
10. Circular Anti-Robinson Matrices for Symmetric Proximity Data
11. Anti-Robinson Matrices for Two-Mode Proximity Data
| Item type | Current library | Collection | Shelving location | Call number | Status | Barcode | |
|---|---|---|---|---|---|---|---|
Reference
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Kalaignar Centenary Library Madurai | ENGLISH-REFERENCE BOOKS | மூன்றாம் தளம் / Third floor | 512.9 HUB (Browse shelf(Opens below)) | Not for loan | 341642 |
Includes bibliography and index.
1. Linear Unidimensional Scaling
2. Linear Multidimensional Scaling
3. Circular Scaling
4. LUS for Two-Mode Proximity Data
II The Representation of Proximity Matrices by Tree Structures
5. Ultrametrics for Symmetric Proximity Data
6. Additive Trees for Symmetric Proximity Data
7. Fitting Multiple Tree Structures to a Symmetric Proximity Matrix
8. Ultrametrics and Additive Trees for Two-Mode (Rectangular) Proximity Data
III The Representation of Proximity Matrices by Structures Dependent on Order (Only)
9. Anti-Robinson Matrices for Symmetric Proximity Data
10. Circular Anti-Robinson Matrices for Symmetric Proximity Data
11. Anti-Robinson Matrices for Two-Mode Proximity Data
This book by Lawrence Hubert, with contributions from Phipps Arabie and Jacqueline Meulman, serves as a practical guide to representing proximity data using MATLAB. It expertly demonstrates M-files for various structural representations of one-mode (symmetric) and two-mode (rectangular) proximity matrices, techniques primarily developed in behavioral sciences but now relevant in fields like bioinformatics and chemometrics. Divided into three parts, the book covers linear and circular scaling with city-block metrics, graph-theoretic tree structures (ultrametrics and additive trees), and order-based representations, particularly anti-Robinson forms, making complex analytical methods accessible through a computational approach.