Abstract
In the Bayesian approach, to describe a prior distribution on the set [0, 1] of all possible probability values, typically, a Beta distribution is used. The fact that there have been many successful applications of this idea seems to indicate that there must be a fundamental reason for selecting this particular family of distributions. In this paper, we show that the selection of this family can indeed be explained if we make reasonable invariance requirements.
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Acknowledgments
This work was supported by the Institute of Geodesy, Leibniz University of Hannover. It was also supported in part by the US National Science Foundation grants 1623190 (A Model of Change for Preparing a New Generation for Professional Practice in Computer Science) and HRD-1242122 (Cyber-ShARE Center of Excellence).
This paper was written when V. Kreinovich was visiting Leibniz University of Hannover.
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Kosheleva, O., Kreinovich, V., Autchariyapanitkul, K. (2021). Why Beta Priors: Invariance-Based Explanation. In: Sriboonchitta, S., Kreinovich, V., Yamaka, W. (eds) Behavioral Predictive Modeling in Economics. Studies in Computational Intelligence, vol 897. Springer, Cham. https://doi.org/10.1007/978-3-030-49728-6_8
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DOI: https://doi.org/10.1007/978-3-030-49728-6_8
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