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Comment on Pisarenko et al. "Characterization of the Tail of the Distribution of Earthquake Magnitudes by Combining the GEV and GPD Descriptions of Extreme Value Theory"

In this short note, I comment on the research of Pisarenko et al. (2014) regarding the extreme value theory and statistics in case of earthquake magnitudes. The link between the generalized extreme value distribution (GEVD) as an asymptotic model for the block maxima of a random variable and the generalized Pareto distribution (GPD) as a model for the peak over thresholds (POT) of the same random variable is presented more clearly. Pisarenko et al. (2014) have inappropriately neglected that the approximations by GEVD and GPD work only asymptotically in most cases. This applies particularly for the truncated exponential distribution (TED), being a popular distribution model for earthquake magnitudes. I explain why the classical models and methods of the extreme value theory and statistics do not work well for truncated exponential distributions. As a consequence, the classical methods should be used for the estimation of the upper bound magnitude and corresponding parameters. Furthermore, different issues of statistical inference of Pisarenko et al. (2014) are commented on and alternatives are proposed. Arguments are presented why GPD and GEVD would work for different types of stochastic earthquake processes in time, and not only for the homogeneous (stationery) Poisson process as assumed by Pisarenko et al. (2014). The crucial point of earthquake magnitudes is the poor convergence of their tail distribution to the GPD, and not the earthquake process in time.