Viertl Statistical Methods for Fuzzy Data

1. Auflage 2011
ISBN: 978-0-470-97456-8
Verlag: John Wiley & Sons
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 268 Seiten, E-Book

Statistical data are not always precise numbers, or vectors, orcategories. Real data are frequently what is called fuzzy. Exampleswhere this fuzziness is obvious are quality of life data,environmental, biological, medical, sociological and economicsdata. Also the results of measurements can be best described byusing fuzzy numbers and fuzzy vectors respectively.
Statistical analysis methods have to be adapted for the analysisof fuzzy data. In this book, the foundations of the description offuzzy data are explained, including methods on how to obtain thecharacterizing function of fuzzy measurement results. Furthermore,statistical methods are then generalized to the analysis of fuzzydata and fuzzy a-priori information.
Key Features:
* Provides basic methods for the mathematical description offuzzy data, as well as statistical methods that can be used toanalyze fuzzy data.
* Describes methods of increasing importance with applications inareas such as environmental statistics and social science.
* Complements the theory with exercises and solutions and isillustrated throughout with diagrams and examples.
* Explores areas such quantitative description of datauncertainty and mathematical description of fuzzy data.
This work is aimed at statisticians working with fuzzy logic,engineering statisticians, finance researchers, and environmentalstatisticians. It is written for readers who are familiar withelementary stochastic models and basic statistical methods.

Autoren/Hrsg.

Viertl, Reinhard

Über Autor(innen)

Reinhard Viertl is Professor of Applied Statistics at Vienna University of Technology.
Professor Viertl has been working on statistical analysis of fuzzy data for about 20 years. He is the author of various publications including 5 books and more than 100 papers.