Statistical methods for fuzzy data
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 b...
| Autor principal: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Chichester, West Sussex :
Wiley
2011.
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| Edición: | 1st edition |
| Colección: | Wiley Series in Probability and Statistics
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628985706719 |
| Sumario: | 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 |
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| Notas: | Description based upon print version of record. |
| Descripción Física: | 1 online resource (270 p.) |
| Bibliografía: | Includes bibliographical references and index. |
| ISBN: | 9781280767548 9786613678317 9780470974421 9780470974414 |
