This project contains Matlab code to estimate an Epidemic Type Aftershock Sequence (ETAS) or ETAS-Incomplete (ETASI) model. The implementation advances the standard ETAS model by enabling anisotropic spatial kernels and accounting for short-term aftershock incompleteness.
User Recommendations:
- Clone or download the repository on your computer
- The package does not need to be "installed". Make sure to include the code folder into the Matlab path.
- You may start using the code with the exemplary earthquake dataset for Southern California, which has been downloaded from the Southern California Earthquake Data Center (https://scedc.caltech.edu/data/alt-2011-dd-hauksson-yang-shearer.html, last accessed on October 25, 2021). You can run the model either for the long-term dataset (1981-2019):
- You find the dataset in data/Catalogs
- You find exemplary polygons for entire Southern California (Pol_CA_Haukson.mat) as well as a 50km-radius polygon around the 2019 Ridgecrest Mw6.4 foreshock event in data/Polygons
- You find exemplary ini files for a long-term, entire Southern California ETASI fit and a short-term fit of the 2019 Ridgecrest Mw6.4 foreshock sequence with two ruptured faults (Grimm et al., 2022)
Please refer to the user manuals for precise instructions on how to use the code.
Citations:
• Christian Grimm implemented the code in Matlab version R2019a.
• The standard functionality of the model is inspired by the implementation in the R package ETAS: Jalilian, A. (2019). ETAS: An R package for fitting the space-time ETAS model to earthquake data, J. Stat. Softw. 88, no. 1, 1–39, doi: 10.18637/jss.v088.c01.
• Additional features such as anisotropic spatial kernels and short-term aftershock incompleteness refer to the model theory described in detail in the following papers:
C. Grimm, M. Käser, S. Hainzl, M. Pagani, and H. Küchenhoff (2021). Improving Earthquake Doublet Frequency Predictions by Modified Spatial Trigger Kernels in the Epidemic-Type Aftershock Sequence (ETAS) Model, Bull. Seismol. Soc. Am. XX, 1–20, doi: 10.1785/0120210097
Hainzl, S. (2021). ETAS-Approach Accounting for Short-Term Incompleteness of Earthquake 753 Catalogs. Bulletin of the Seismological Society of America. doi: 10.1785/0120210146.
C. Grimm, S. Hainzl, M. Käser, and H. Küchenhoff (2022). Solving three major biases of the ETAS model to improve forecasts of the 2019 Ridgecrest sequence., doi: https://doi.org/10.21203/rs.3.rs-1128731/v1 (accepted)