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Fuzzy set representation of a prior distribution

Glen Meeden

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Abstract

In the subjective Bayesian approach uncertainty is described by a prior distribution chosen by the statistician. Fuzzy set theory is another way of representing uncertainty. Here we give a decision theoretic approach which allows a Bayesian to convert their prior distribution into a fuzzy set membership function. This yields a formal relationship between these two different methods of expressing uncertainty.

Chapter information

Source
Bertrand Clarke and Subhashis Ghosal, eds., Pushing the Limits of Contemporary Statistics: Contributions in Honor of Jayanta K. Ghosh (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2008), 82-88

Dates
First available in Project Euclid: 28 April 2008

Permanent link to this document
https://projecteuclid.org/euclid.imsc/1209398462

Digital Object Identifier
doi:10.1214/074921708000000075

Mathematical Reviews number (MathSciNet)
MR2459218

Subjects
Primary: 62F15: Bayesian inference
Secondary: 62C05: General considerations

Keywords
Bayesian inference fuzzy sets prior distribution

Rights
Copyright © 2008, Institute of Mathematical Statistics

Citation

Meeden, Glen. Fuzzy set representation of a prior distribution. Pushing the Limits of Contemporary Statistics: Contributions in Honor of Jayanta K. Ghosh, 82--88, Institute of Mathematical Statistics, Beachwood, Ohio, USA, 2008. doi:10.1214/074921708000000075. https://projecteuclid.org/euclid.imsc/1209398462


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References

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