This book presents the most recent methods for analyzing and visualizing symbolic data. It generalizes classical methods of exploratory, statistical and graphical data analysis to the case of complex data. Several benchmark examples from National Statistical Offices illustrate the usefulness of the methods. The book contains an extensive bibliography and a subject index.
This volume contains a selection of papers presented during the biennial meeting of the CLAssification and Data Analysis Group (CLADAG) of the Societa Italiana di Statistica which was orga nized by the Istituto di Statistica of the Universita degli Studi di Palermo and held in the Palazzo Steri in Palermo on July 5-6, 2001. For this conference, and after checking the submitted 4 page abstracts, 54 papers were admitted for presentation. They covered a large range of topics from multivariate data analysis, with special emphasis on classification and clustering, computa tional statistics, time series analysis, and applications in various classical or recent domains. A two-fold careful reviewing process led to the selection of 22 papers which are presented in this vol ume. They convey either a new idea or methodology, present a new algorithm, or concern an interesting application. We have clustered these papers into five groups as follows: 1. Classification Methods with Applications 2. Time Series Analysis and Related Methods 3. Computer Intensive Techniques and Algorithms 4. Classification and Data Analysis in Economics 5. Multivariate Analysis in Applied Sciences. In each section the papers are arranged in alphabetical order. The editors - two of them the organizers of the CLADAG confer ence - would like to express their gratitude to the authors whose enthusiastic participation made the meeting possible and very successful.
This volume features 45 articles addressing theoretical aspects, methodological advancements, and practical applications in classification and clustering, statistical and computational data analysis, and knowledge structures for databases. Selected from around 140 papers presented at the 19th Annual Conference of the Gesellschaft für Klassifikation, hosted by W. Polasek at the University of Basel in March 1995, the articles are organized into several chapters: 1) Classification and clustering (8), 2) Uncertainty and fuzziness (5), 3) Methods of data analysis and applications (7), 4) Statistical models and methods (4), 5) Bayesian learning (5), 6) Conceptual classification, knowledge ordering, and information systems (12), and 7) Linguistics and dialectometry (4). The chapters are interrelated, highlighting analogies and distinctions among classification principles in statistics and information sciences, the advantages of comparing conceptual and mathematical approaches, and the diverse practical applications discussed. For reader convenience, a brief review of the content is provided.