Analysis of Symbolic Data

1. Front Matter

   Pages i-xviii

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2. Symbolic Data Analysis and the SODAS Project: Purpose, History, Perspective

   • Edwin Diday

   Pages 1-23

3. The Classical Data Situation

   • Hans-Hermann Bock

   Pages 24-38

4. Symbolic Data

   • Hans-Hermann Bock

   Pages 39-53

5. Symbolic Objects

   • Hans-Hermann Bock, Edwin Diday

   Pages 54-77

6. Generation of Symbolic Objects from Relational Databases

   • Véronique Stéphan, Georges Hébrail, Yves Lechevallier

   Pages 78-105

7. Descriptive Statistics for Symbolic Data

   • Patrice Bertrand, Françoise Goupil

   Pages 106-124

8. Visualizing and Editing Symbolic Objects

   • Monique Noirhomme-Fraiture, Manuel Rouard

   Pages 125-138

9. Similarity and Dissimilarity

   • F. Esposito, D. Malerba, V. Tamma, H. H. Bock

   Pages 139-197

10. Symbolic Factor Analysis

    • Hans-Hermann Bock, A. Chouakria, P. Cazes, E. Diday

    Pages 198-233

11. Discrimination: Assigning Symbolic Objects to Classes

    • Jean-Paul Rasson, Sandrine Lissoir

    Pages 234-293

12. Clustering Methods for Symbolic Objects

    • Marie Chavent, Hans-Hermann Bock

    Pages 294-341

13. Symbolic Approaches for Three-way Data

    • Mireille Gettler-Summa, Catherine Pardoux

    Pages 342-354

14. Illustrative Benchmark Analyses

    • Raymond Bisdorff

    Pages 355-385

15. The SODAS Software Package

    • Alain Morineau

    Pages 386-391

16. Back Matter

    Pages 392-425

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Raymond Bisdorff CRP-GL, Luxembourg The development of the SODAS software based on symbolic data analysis was extensively described in the previous chapters of this book. It was accompanied by a series of benchmark activities involving some official statistical institutes throughout Europe. Partners in these benchmark activities were the National Statistical Institute (INE) of Portugal, the Instituto Vasco de Estadistica Euskal (EUSTAT) from Spain, the Office For National Statistics (ONS) from the United Kingdom, the Inspection Generale de la Securite Sociale (IGSS) from Luxembourg 1 and marginally the University of Athens . The principal goal of these benchmark activities was to demonstrate the usefulness of symbolic data analysis for practical statistical exploitation and analysis of official statistical data. This chapter aims to report briefly on these activities by presenting some signifi­ cant insights into practical results obtained by the benchmark partners in using the SODAS software package as described in chapter 14 below.

• Data Mining
• Datenanalyse
• Descriptive statistics
• Factor analysis
• Probability distribution
• Statistik
• calculus
• classification
• data analysis
• databases
• knowledge discovery
• principal component analysis
• sets
• statistics
• data structures

• Institut für Statistik und Wirtschaftsmathematik, RWTH Aachen, Aachen, Germany

  Hans-Hermann Bock

• LISE CEREMADE, Université Paris IX-Dauphine, Paris Cedex 16, France

  Edwin Diday

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