Bayesian Estimation of the ETAS Model for Earthquake Occurrences

@article{Ross2021BayesianEO,
  title={Bayesian Estimation of the ETAS Model for Earthquake Occurrences},
  author={Gordon J. Ross},
  journal={Bulletin of the Seismological Society of America},
  year={2021},
  volume={111},
  pages={1473-1480}
}
  • Gordon J. Ross
  • Published 1 June 2021
  • Computer Science, Mathematics, Physics
  • Bulletin of the Seismological Society of America
The Epidemic Type Aftershock Sequence (ETAS) model is one of the most widelyused approaches to seismic forecasting. However most studies of ETAS use point estimates for the model parameters, which ignores the inherent uncertainty that arises from estimating these from historical earthquake catalogs, resulting in misleadingly optimistic forecasts. In contrast, Bayesian statistics allows parameter uncertainty to be explicitly represented, and fed into the forecast distribution. Despite its… 

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