Geodesic
Fuzzy data in statistics
Kybernetika, Tome 43 (2007) no. 4, pp. 491-502 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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The development of effective methods of data processing belongs to important challenges of modern applied mathematics and theoretical information science. If the natural uncertainty of the data means their vagueness, then the theory of fuzzy quantities offers relatively strong tools for their treatment. These tools differ from the statistical methods and this difference is not only justifiable but also admissible. This relatively brief paper aims to summarize the main fuzzy approaches to vague data processing, to discuss their main advantages and also their essential limitations, and to specify their place in the wide scale of information and knowledge processing methods effective for vague data.
The development of effective methods of data processing belongs to important challenges of modern applied mathematics and theoretical information science. If the natural uncertainty of the data means their vagueness, then the theory of fuzzy quantities offers relatively strong tools for their treatment. These tools differ from the statistical methods and this difference is not only justifiable but also admissible. This relatively brief paper aims to summarize the main fuzzy approaches to vague data processing, to discuss their main advantages and also their essential limitations, and to specify their place in the wide scale of information and knowledge processing methods effective for vague data.
Classification : 03E72, 08A72, 62A01, 62–07
Keywords: fuzzy quantity; extension principle; fuzzy data 
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     author = {Mare\v{s}, Milan},
     title = {Fuzzy data in statistics},
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     language = {en},
     url = {http://geodesic.mathdoc.fr/item/KYB_2007_43_4_a9/}
}
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Mareš, Milan. Fuzzy data in statistics. Kybernetika, Tome 43 (2007) no. 4, pp. 491-502. http://geodesic.mathdoc.fr/item/KYB_2007_43_4_a9/

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