Distribution of Maximum Earthquake Magnitudes in Future Time Intervals, Application to the Seismicity of Japan (1923-2007)
V.F. Pisarenko, D. Sornette, M.V.Rodkin

TL;DR
This paper introduces a robust statistical method to estimate the distribution of maximum earthquake magnitudes in future intervals, applied to Japan's seismic data, providing more stable predictions than traditional maximum magnitude estimates.
Contribution
The paper adapts a new extreme value theory-based method to estimate future maximum earthquake magnitudes, improving robustness over traditional approaches.
Findings
Estimated parameters for Japan's earthquake data (1923-2007).
Predicted maximum magnitudes for future intervals with reduced uncertainty.
Compared new quantile-based estimates with traditional maximum magnitude, showing increased stability.
Abstract
We modify the new method for the statistical estimation of the tail distribution of earthquake seismic moments introduced by Pisarenko et al. [2009] and apply it to the earthquake catalog of Japan (1923-2007). The method is based on the two main limit theorems of the theory of extreme values and on the derived duality between the Generalized Pareto Distribution (GPD) and Generalized Extreme Value distribution (GEV). We obtain the distribution of maximum earthquake magnitudes in future time intervals of arbitrary duration tau. This distribution can be characterized by its quantile Qq(tau) at any desirable statistical level q. The quantile Qq(tau) provides a much more stable and robust characteristic than the traditional absolute maximum magnitude Mmax (Mmax can be obtained as the limit of Qq(tau) as q tends to 1, and tau tends to infinity). The best estimates of the parameters governing…
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