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Generalized Bayes’ theorem for non-precise a-priori distribution

Author

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  • Reinhard Viertl
  • Dietmar Hareter

Abstract

A-priori knowledge in form of one exact probability distribution on the parameter space is questionable. For more general forms of a-priori information so-called non-precise a-priori densities are a suitable quantitative description. This kind of a-priori information can be used in a generalized version of Bayes’ theorem. Copyright Springer-Verlag 2004

Suggested Citation

  • Reinhard Viertl & Dietmar Hareter, 2004. "Generalized Bayes’ theorem for non-precise a-priori distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 59(3), pages 263-273, June.
    • Handle: RePEc:spr:metrik:v:59:y:2004:i:3:p:263-273
    DOI: 10.1007/s001840300283
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    Cited by:

    1. Shapiro, Arnold F., 2009. "Fuzzy random variables," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 307-314, April.
    2. Viertl, Reinhard, 2006. "Univariate statistical analysis with fuzzy data," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 133-147, November.
    3. Hryniewicz, Olgierd, 2016. "Bayes statistical decisions with random fuzzy data—an application in reliability," Reliability Engineering and System Safety, Elsevier, vol. 151(C), pages 20-33.

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