Earthquake forecasting based on data assimilation: sequential Monte Carlo methods for renewal point processes

@inproceedings{Werner2011EarthquakeFB,
  title={Earthquake forecasting based on data assimilation: sequential Monte Carlo methods for renewal point processes},
  author={Maximilian J. Werner and Kayo Ide},
  year={2011}
}
Data assimilation is routinely employed in meteorology, engineering and computer sciences to optimally combine noisy observations with prior model information for obtaining better estimates of a state, and thus better forecasts, than achieved by ignoring data uncertainties. Earthquake forecasting, too, suffers from measurement errors and partial model information and may thus gain significantly from data assimilation. We present perhaps the first fully implementable data assimilation method for… CONTINUE READING
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