Leila Mizrahi, Shyam Nandan, Stefan Wiemer 2021;
Embracing Data Incompleteness for Better Earthquake Forecasting.
Journal of Geophysical Research: Solid Earth; doi: https://doi.org/10.1029/2021JB022379
To cite the code, please cite the article.
For more documentation on the code, see the (supporting information of the) article.
For general ETAS, or ETAS with long-term variations of completeness, see ETAS.
In case of questions or comments, contact me: [email protected].
- inversion.py: PETAI algorithm to estimate ETAS and detection parameters.
- simulation.py: Catalog simulation given ETAS parameters and estimated incompleteness.
- data/synthetic_catalog.csv: example synthetic catalog.
- invert_petai.py: run example PETAI inversion on data/synthetic_catalog.csv.
- simulate_catalog_continuation.py: simulate one example catalog continuation of data/synthetic_catalog.csv, using the parameters and incompleteness estimated when running invert_petai.py.
Just in case, here is my pip freeze:
- geopandas==0.9.0
- numpy==1.19.1
- pandas==1.1.1
- pynverse==0.1.4.4
- pyproj==3.0.1
- scipy==1.5.2