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On the foundations of bayesianism
RISE - Research Institutes of Sweden, ICT, SICS.
2001 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We discuss precise assumptions entailing Bayesianism in the line of investigations started by Cox, and relate them to a recent critique by Halpern. We show that every finite model which cannot be rescaled to probability violates a natural and simple refinability principle. A new condition, separability, was found sufficient and necessary for rescalability of infinite models.We finally characterise the acceptable ways to handle uncertainty in infinite models based on Cox's assumptions. Certain closure properties must be assumed before all the axioms of ordered fields are satisfied. Once this is done, a proper plausibility model can be embedded in an ordered field containing the reals, namely either standard probability (field of reals) for a real valued plausibility model, or extended probability (field of reals and infinitesimals) for an ordered plausibility model.

Place, publisher, year, edition, pages
Springer, 2001, 1. , p. 10
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:ri:diva-22588ISBN: 0-7354-0004-0 (print)OAI: oai:DiVA.org:ri-22588DiVA, id: diva2:1042153
Conference
Twentieth International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, 8-13 July 2000, Gif sur Yvette, France
Note

Published by Springer. ISBN 0-7354-0004-0.

Available from: 2016-10-31 Created: 2016-10-31 Last updated: 2018-01-14Bibliographically approved

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CiteExportLink to record
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  • apa
  • harvard1
  • ieee
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Language
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Output format
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