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| Titel |
Estimating ETAS: the effects of truncation, missing data, and model
assumptions |
| VerfasserIn |
Stefanie Seif, Arnaud Mignan, Jeremy Zechar, Maximilian Werner, Stefan Wiemer |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250133322
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| Publikation (Nr.) |
 EGU/EGU2016-13919.pdf |
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| Zusammenfassung |
| 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 of the
limits of, and influences on, its estimation. What has been established is that ETAS
parameter estimates are influenced by missing data (e.g., earthquakes are not reliably
detected during lively aftershock sequences) and by simplifying assumptions (e.g., that
aftershocks are isotropically distributed). In this article, we investigate the effect of
truncation: how do parameter estimates depend on the cut-off magnitude, Mcut, above
which parameters are estimated? We analyze catalogs from southern California and
Italy and find that parameter variations as a function of Mcut are caused by (i)
changing sample size (which affects e.g. Omori’s cconstant) or (ii) 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 Omoris c-value are
significantly changed only for low Mcut=2.5. 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 six. |
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