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On the Analysis of Fuzzy Life Times and Quality of Life Data

In: Probability, Statistics and Modelling in Public Health

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  • Reinhard Viertl

    (Vienna University of Technology)

Abstract

Summary Life times, health data, and general quality of life data are often not adequately represented by precise numbers or classes. Such data are called nonprecise or fuzzy, because their quantitative characterization is possible by so-called non-precise numbers. To analyze such data a more general concept than fuzzy numbers from the theory of fuzzy sets is necessary. A suitable concept are so-called non-precise numbers. Generalized methods to analyze such data are available, and basic methods for that are described in the paper.

Suggested Citation

  • Reinhard Viertl, 2006. "On the Analysis of Fuzzy Life Times and Quality of Life Data," Springer Books, in: Mikhail Nikulin & Daniel Commenges & Catherine Huber (ed.), Probability, Statistics and Modelling in Public Health, pages 446-451, Springer.
    • Handle: RePEc:spr:sprchp:978-0-387-26023-5_30
    DOI: 10.1007/0-387-26023-4_30
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