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"Not Only Defended But Also Applied": The Perceived Absurdity of Bayesian Inference

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  • Andrew Gelman
  • Christian P. Robert

Abstract

The missionary zeal of many Bayesians of old has been matched, in the other direction, by an attitude among some theoreticians that Bayesian methods were absurd-not merely misguided but obviously wrong in principle. We consider several examples, beginning with Feller's classic text on probability theory and continuing with more recent cases such as the perceived Bayesian nature of the so-called doomsday argument. We analyze in this note the intellectual background behind various misconceptions about Bayesian statistics, without aiming at a complete historical coverage of the reasons for this dismissal.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:amstat:v:67:y:2013:i:1:p:1-5
    DOI: 10.1080/00031305.2013.760987
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    Cited by:

    1. 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.
    2. Eibich, Peter & Ziebarth, Nicolas, 2014. "Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 49, pages 305-320.
    3. Seites-Rundlett, William & Bashar, Mohammad Z. & Torres-Machi, Cristina & Corotis, Ross B., 2022. "Combined evidence model to enhance pavement condition prediction from highly uncertain sensor data," Reliability Engineering and System Safety, Elsevier, vol. 217(C).

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