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Description
Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively.
Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy measurement results. Furthermore, statistical methods are then generalized to the analysis of fuzzy data and fuzzy a-priori information.
Key Features: Provides basic methods for the mathematical description of fuzzy data, as well as statistical methods that can be used to analyze fuzzy data. Describes methods of increasing importance with applications in areas such as environmental statistics and social science. Complements the theory with exercises and solutions and is illustrated throughout with diagrams and examples. Explores areas such quantitative description of data uncertainty and mathematical description of fuzzy data.
This work is aimed at statisticians working with fuzzy logic, engineering statisticians, finance researchers, and environmental statisticians. It is written for readers who are familiar with elementary stochastic models and basic statistical methods.
Pages
272 pages
Collection
Wiley Series in Probability and Statistics
Parution
2011-01-25
Marque
Wiley
EAN papier
9780470699454
EAN PDF
9780470974421

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
272
Taille du fichier
6892 Ko
Prix
99,12 €
EAN EPUB
9780470974568

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
272
Taille du fichier
4608 Ko
Prix
99,12 €