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Fuzzy Hypotheses Testing with Fuzzy Data: A Bayesian Approach

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Book cover Advances in Soft Computing — AFSS 2002 (AFSS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2275))

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Abstract

In hypotheses testing, such as other statistical problems, we may confront with imprecise concepts. One case is a situation in which both hypotheses and observations are imprecise. In this paper, using fuzzy set theory for formulation of imprecise hypotheses and observations, we analyze mentioned problem on the basis of a Bayesian method.

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References

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Author information

Authors and Affiliations

  1. School of Mathematics, Isfahan University of Technology, 84154, Isfahan, Iran

    Seyed Mahmoud Taheri

  2. Dept. of Stat., Shiraz University, Shiraz, Iran

    Javad Behboodian

Authors
  1. Seyed Mahmoud Taheri
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  2. Javad Behboodian
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Editor information

Editors and Affiliations

  1. Electronics and Communication Sciences Unit, Indian Statistical Institute, 203 B.T. Road, 700108, Calcutta, India

    Nikhil R. Pal

  2. Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako, Japan

    Michio Sugeno

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© 2002 Springer-Verlag Berlin Heidelberg

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Taheri, S.M., Behboodian, J. (2002). Fuzzy Hypotheses Testing with Fuzzy Data: A Bayesian Approach. In: Pal, N.R., Sugeno, M. (eds) Advances in Soft Computing — AFSS 2002. AFSS 2002. Lecture Notes in Computer Science(), vol 2275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45631-7_73

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  • DOI: https://doi.org/10.1007/3-540-45631-7_73

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43150-3

  • Online ISBN: 978-3-540-45631-5

  • eBook Packages: Springer Book Archive

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