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Bayesian earthquake forecasting approach based on the epidemic type aftershock sequence model.
- Source :
-
Earth, Planets & Space . 5/24/2024, Vol. 76 Issue 1, p1-16. 16p. - Publication Year :
- 2024
-
Abstract
- The epidemic type aftershock sequence (ETAS) model is used as a baseline model both for earthquake clustering and earthquake prediction. In most forecast experiments, the ETAS parameters are estimated based on a short and local catalog, therefore the model parameter optimization carried out by means of a maximum likelihood estimation may be not as robust as expected. We use Bayesian forecast techniques to solve this problem, where non-informative flat prior distributions of the parameters is adopted to perform forecast experiments on 3 mainshocks occurred in Southern California. A Metropolis–Hastings algorithm is employed to sample the model parameters and earthquake events. We also show, through forecast experiments, how the Bayesian inference allows to obtain a probabilistic forecast, differently from one obtained via MLE. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13438832
- Volume :
- 76
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Earth, Planets & Space
- Publication Type :
- Academic Journal
- Accession number :
- 177463650
- Full Text :
- https://doi.org/10.1186/s40623-024-02021-8