TY  - BOOK
AU  - Blasius,Jorg
AU  - Greenacre,Michael
TI  - Visualization and verbalization of data
T2  - Computer science & data analysis series
SN  - 9781466589803 (hardback)
U1  - 000SA.07 23
PY  - 2014///
CY  - Boca Raton : 
PB  - CRC Press,   
KW  - Information visualization
KW  - Correspondence analysis (Statistics)
KW  - Multiple comparisons (Statistics)
N1  - Includes bibliographical references and index; Section I: History of Correspondence Analysis and Related Methods 
1. Some Prehistory of CARME: Visual Language and Visual Thinking, Michael Friendly and Matthew Sigal--
2. Some History of Algebraic Canonical Forms and Data Analysis, John C. Gower--
3. Historical Elements of Correspondence Analysis and Multiple Correspondence Analysis, Ludovic Lebart and Gilbert Saporta-- 4. History of Nonlinear Principal Component Analysis, Jan de Leeuw--
5. History of Canonical Correspondence Analysis, Cajo J.F. ter Braak--
6.  History of Multiway Component Analysis and Three-Way Correspondence Analysis, Pieter M. Kroonenberg--
7. Past, Present, and Future of Multidimensional Scaling, Patrick J.F. Groenen and Ingwer Borg--
8. History of Cluster Analysis, Fionn Murtagh--

Section II: Contribution of Benzecri and the French School 
9. Simple Correspondence Analysis, Pierre Cazes-- 
10. Distributional Equivalence and Linguistics, Monica Becue-Bertaut--
11. Multiple Correspondence Analysis, Francois Husson and Julie Josse--
12. Structured Data Analysis, Brigitte Le Roux--
13. Empirical Construction of Bourdieu's Social Space, Jorg Blasius and Andreas Schmitz--
14. Multiple Factor Analysis: General Presentation and Comparison with Statis, Jerome Pages--
15. Data Doubling and Fuzzy Coding, Michael Greenacre-- 
16. Symbolic Data Analysis: A Factorial Approach Based on Fuzzy Coded Data, Rosanna Verde and Edwin Diday--
17. Group Average Linkage Compared to Ward's Method in Hierarchical Clustering, Maurice Roux--
18. Analyzing a Pair of Tables: Co-Inertia Analysis and Duality Diagrams, Stephane Dray--
References--
Index
N2  - "This volume presents an overview of the state of the art in data visualization, encompassing correspondence analysis, nonlinear principal component analysis, cluster analysis, multidimensional scaling, and much more. It covers the historical development of each topic along with modern techniques and future research directions. To illustrate the methods, the book incorporates many real data examples and software implementations. Each chapter is written by leading researchers in the field and thoroughly edited to ensure coherence and consistency"--
ER  -