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...
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| Format: | eBook |
| Language: | English |
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Chichester, West Sussex
Wiley
2011
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| Collection: | O'Reilly - Collection details see MPG.ReNa |
| Summary: | 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 m |
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| Physical Description: | xii, 256 pages illustrations |
| ISBN: | 0470974427 9780470974421 0470974419 9781280767548 9780470974568 9780470974414 1280767545 0470974567 |