Abstract
Chilean seismic activity is one of the strongest in the world. As already shown in previous papers, seismic activity can be usefully described by a space–time branching process, such as the ETAS (Epidemic Type Aftershock Sequences) model, which is a semiparametric model with a large time-scale component for the background seismicity and a small time-scale component for the triggered seismicity. The use of covariates can improve the description of triggered seismicity in the ETAS model, so in this paper, we study the Chilean seismicity separately for the North and South area, using some GPS-related data observed together with ordinary catalog data. Our results show evidence that the use of some covariates can improve the fitting of the ETAS model.
Original language | English |
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Article number | 9143 |
Journal | Applied Sciences (Switzerland) |
Volume | 11 |
Issue number | 19 |
DOIs | |
Publication status | Published - 1 Oct 2021 |
Keywords
- Covariates
- ETAS model
- Model selection
- Semiparametric models
- Triggered seismicity
ASJC Scopus subject areas
- General Materials Science
- Instrumentation
- General Engineering
- Process Chemistry and Technology
- Computer Science Applications
- Fluid Flow and Transfer Processes