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Sensitivity of Decisions to Probability Estimation Errors: A Reexamination

Author

Listed:
  • Peter C. Fishburn

    (Advanced Research Department, Research Analysis Corporation)

  • Allan H. Murphy

    (Department of Meteorology and Oceanography, University of Michigan)

  • Herbert H. Isaacs

    (Herbert H. Isaacs, Research and Consulting, Inc.)

Abstract

In the subjective expected utility model for decision making under uncertainty the decision maker often has difficulty assigning to the states probabilities with which he is completely satisfied. Six approaches that might be used to help the decision maker resolve his uncertainty about the values of his state probabilities are outlined. One approach tells the decision maker how much he must perturb his initial probability estimate in order to change his maximum expected utility alternative from the alternative originally best under the initial estimate. This approach is examined in greater detail and an iterative algorithm for solving the minimum-perturbation problem is presented.

Suggested Citation

  • Peter C. Fishburn & Allan H. Murphy & Herbert H. Isaacs, 1968. "Sensitivity of Decisions to Probability Estimation Errors: A Reexamination," Operations Research, INFORMS, vol. 16(2), pages 254-267, April.
    • Handle: RePEc:inm:oropre:v:16:y:1968:i:2:p:254-267
    DOI: 10.1287/opre.16.2.254
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    Cited by:

    1. Stanca, Lorenzo, 2023. "Robust Bayesian choice," Mathematical Social Sciences, Elsevier, vol. 126(C), pages 94-106.
    2. Ringuest, Jeffrey L., 1997. "LP-metric sensitivity analysis for single and multi-attribute decision analysis," European Journal of Operational Research, Elsevier, vol. 98(3), pages 563-570, May.
    3. James C. Felli & Gordon B. Hazen, 1998. "Sensitivity Analysis and the Expected Value of Perfect Information," Medical Decision Making, , vol. 18(1), pages 95-109, January.
    4. Tao Huang & J. Eric Bickel, 2019. "Sparse Probability Assessment Heuristic Based on Orthogonal Matching Pursuit," Decision Analysis, INFORMS, vol. 16(4), pages 281-300, December.
    5. Stanca Lorenzo, 2023. "Robust Bayesian Choice," Working papers 079, Department of Economics, Social Studies, Applied Mathematics and Statistics (Dipartimento di Scienze Economico-Sociali e Matematico-Statistiche), University of Torino.
    6. Lorenzo Stanca, 2023. "Robust Bayesian Choice," Carlo Alberto Notebooks 690 JEL Classification: C, Collegio Carlo Alberto.

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