The Epidemic‐Type Aftershock Sequence (ETAS) model is widely used to describe the occurrence of earthquakes in space and time, but there has been little discussion dedicated to the limits of, and influences on, its estimation. Among the possible influences we emphasize in this article the effect of the cutoff magnitude, Mcut, above which parameters are estimated; the finite length of earthquake catalogs; and missing data (e.g., during lively aftershock sequences). We analyze catalogs from Southern California and Italy and find that some parameters vary as a function of Mcut due to changing sample size (which affects, e.g., Omori's c constant) or an intrinsic dependence on Mcut (as Mcut increases, absolute productivity and background rate decrease). We also explore the influence of another form of truncation—the finite catalog length—that can bias estimators of the branching ratio. Being also a function of Omori's p value, the true branching ratio is underestimated by 45% to 5% for 1.05 < p < 1.2. Finite sample size affects the variation of the branching ratio estimates. Moreover, we investigate the effect of missing aftershocks and find that the ETAS productivity parameters (α and K0) and the Omori's c and p values are significantly changed for Mcut < 3.5. We further find that conventional estimation errors for these parameters, inferred from simulations that do not account for aftershock incompleteness, are underestimated by, on average, a factor of 8.
Laboratory experiments highlight a systematic b value decrease during the stress increase period before failure, and some large natural events are known to show a precursory decrease in the b value. However, short‐term forecast models currently consider only the generic probability that an event can trigger subsequent seismicity in the near field. While the probability increase over a stationary Poissonian background is substantial, selected case studies have shown through cost‐benefit analysis that the absolute main shock probability remains too low to warrant significant mitigation actions. We analyze the probabilities considering both changes in the seismicity rates and temporal changes in the b value. The precursory b value decrease in the 2009 L'Aquila case results in an additional fiftyfold probability increase for a M6.3 event. Translated into time‐varying hazard and risk, these changes surpass the cost‐benefit threshold for short‐term evacuation.
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