Comparison Between Bayesian and Frequentist Tail Probability Estimates
Volume 1, Issue 2 (2023), pp. 208–215
Pub. online: 22 June 2023
Type: Methodology Article
Open Access
Open Access
Area: Statistical Methodology
Accepted
30 May 2023
30 May 2023
Published
22 June 2023
22 June 2023
Abstract
Tail probability plays an important part in the extreme value theory. Sometimes the conclusions from two approaches for estimating the tail probability of extreme events, the Bayesian and the frequentist methods, can differ a lot. In 1999, a rainfall that caused more than 30,000 deaths in Venezuela was not captured by the simple frequentist extreme value techniques. However, this catastrophic rainfall was not surprising if the Bayesian inference was used to allow for parameter uncertainty and the full available data was exploited [4].
In this paper, we investigate the reasons that the Bayesian estimator of the tail probability is always higher than the frequentist estimator. Sufficient conditions for this phenomenon are established both by using Jensen’s Inequality and by looking at Taylor series approximations, both of which point to the convexity of the distribution function.
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