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Updating beliefs about variables given new information on how those variables relate

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  • Bordley, Robert
  • Bier, Vicki

Abstract

Bayesian techniques specify how to update beliefs about a variable given information on that variable or related variables. In many cases, statistical analyses also provide information about the relationship between variables, but the Borel Paradox prohibits many natural ways of updating beliefs conditioned on information about a relationship. This paper presents a method by which beliefs can be updated without violating the Borel Paradox under certain circumstances. We apply our approach to relationships specified by a statistical model (i.e., regression), and relationships described by statistical simulation.

Suggested Citation

  • Bordley, Robert & Bier, Vicki, 2009. "Updating beliefs about variables given new information on how those variables relate," European Journal of Operational Research, Elsevier, vol. 193(1), pages 184-194, February.
    • Handle: RePEc:eee:ejores:v:193:y:2009:i:1:p:184-194
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    References listed on IDEAS

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    1. Robert L. Winkler, 1981. "Combining Probability Distributions from Dependent Information Sources," Management Science, INFORMS, vol. 27(4), pages 479-488, April.
    2. Schweder, T. & Hjort, N.L., 1996. "Bayesian Synthesis or Likelihood Synthesis - What Does the Borel Paradox Say?," Memorandum 1996_013, Oslo University, Department of Economics.
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    Cited by:

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    2. Robert F. Bordley, 2023. "Lessons for Decision-Analysis Practice from the Automotive Industry," Interfaces, INFORMS, vol. 53(3), pages 240-246, May.

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