The strongest aftershock in seismic models of epidemic type
George Molchan, Elisa Varini

TL;DR
This paper analyzes the distribution of the strongest aftershock magnitude in epidemic-type aftershock models (ETAS) with various distributions, revealing how different regimes and parameters influence the limiting distribution.
Contribution
It extends the ETAS model analysis to a broad class of distributions for aftershock counts, deriving the limiting distribution of the strongest aftershock magnitude under different regimes.
Findings
The limiting distribution depends on the distribution class and regime.
Geometric distribution yields a logistic law for the strongest aftershock.
Poisson distribution results in a Gumbel type 1 law.
Abstract
We consider an epidemic-type aftershock model (ETAS()) for a large class of distributions determining the number of direct aftershocks. This class includes Poisson, Geometric, Negative Binomial distributions and many other. Assuming an exponential form of the productivity and magnitude laws, we find a limiting distribution of the strongest aftershock magnitude when the initial cluster event is large. The regime can be either subcritical or critical; the initial event can be dominant in size or not. In the subcritical regime, the mode of the limiting distribution is determined by the parameters of productivity and the magnitude laws; the shape of this distribution is not universal and is effectively determined by . For example, the Geometric -distribution generates the logistic law, and the Poisson distribution (studied earlier) generates the Gumbel type 1 law.…
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Taxonomy
Topicsearthquake and tectonic studies · Financial Risk and Volatility Modeling · Complex Systems and Time Series Analysis
