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The Need for Adding Judgment in Bayesian Prediction

Author

Listed:
  • Thomas L. Saaty

    (Joseph M. Katz Graduate School of Business and College of Business, University of Pittsburgh, Mervis Hall, Pittsburgh, PA, US)

  • Lei Zhang

    (School of Economics and Management, Beijing Jiaotong University, No. 3, Shangyuancun, Haidian District, Beijing, China)

Abstract

There are many examples of successful application of the famous Bayes’ theorem to forecast the outcome of causes or influences of events. However, there are also many examples of failures of just using probabilities and statistics without also using judgments in each particular application. This is particularly true in medical diagnoses and in sports. The extension we proposed found a way to calculate probabilities combining logical inference of data and judgment. This research extends the use of Bayes’ theorem by incorporating judgments within the framework of the frequently used decision theory, the analytic network process (ANP) and illustrates its use with an application.

Suggested Citation

  • Thomas L. Saaty & Lei Zhang, 2016. "The Need for Adding Judgment in Bayesian Prediction," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 733-761, July.
    • Handle: RePEc:wsi:ijitdm:v:15:y:2016:i:04:n:s0219622016400010
    DOI: 10.1142/S0219622016400010
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    References listed on IDEAS

    as
    1. Wen-chuan Wang & Kwok-wing Chau & Dong-mei Xu & Xiao-Yun Chen, 2015. "Improving Forecasting Accuracy of Annual Runoff Time Series Using ARIMA Based on EEMD Decomposition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2655-2675, June.
    2. repec:dau:papers:123456789/11069 is not listed on IDEAS
    3. Saaty, Thomas L. & Takizawa, Masahiro, 1986. "Dependence and independence: From linear hierarchies to nonlinear networks," European Journal of Operational Research, Elsevier, vol. 26(2), pages 229-237, August.
    4. Andrew Gelman & Christian P. Robert, 2013. ""Not Only Defended But Also Applied": The Perceived Absurdity of Bayesian Inference," The American Statistician, Taylor & Francis Journals, vol. 67(1), pages 1-5, February.
    5. Thomas L. Saaty & Luis G. Vargas, 1998. "Diagnosis with Dependent Symptoms: Bayes Theorem and the Analytic Hierarchy Process," Operations Research, INFORMS, vol. 46(4), pages 491-502, August.
    6. Thomas L. Saaty, 2006. "The Analytic Network Process," International Series in Operations Research & Management Science, in: Decision Making with the Analytic Network Process, chapter 0, pages 1-26, Springer.
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    Cited by:

    1. Liansheng Sang & Jun Wang & Jueyi Sui & Mauricio Dziedzic, 2022. "A New Approach for Dam Safety Assessment Using the Extended Cloud Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 5785-5798, December.

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