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A random effects epidemic-type aftershock sequence model.

Feng-Chang Lin1

  • 1Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States.

Computational Statistics & Data Analysis
|September 17, 2013
PubMed
Summary
This summary is machine-generated.

This study extends the epidemic-type aftershock sequence (ETAS) model using random effects. The enhanced model with positive stable random effects better fits earthquake data than the original ETAS model.

Keywords:
Doubly stochastic self-exciting processETAS modelEarthquake sequenceMarginalized intensityRandom effects

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Area of Science:

  • Seismology
  • Statistical Modeling
  • Point Processes

Background:

  • The temporal epidemic-type aftershock sequence (ETAS) model is widely used for earthquake aftershock forecasting.
  • Existing models may not fully capture the complexities of earthquake sequences, necessitating extensions.

Purpose of the Study:

  • To introduce and evaluate an extended ETAS model incorporating random effects.
  • To compare the performance of the extended model with positive stable and gamma random effects against the original ETAS model.

Main Methods:

  • The proposed model is a doubly stochastic self-exciting point process with a randomly scaled deterministic function.
  • Estimation utilizes maximum likelihood with marginalized intensity.
  • Model performance is assessed through simulation experiments and application to a real earthquake sequence.

Main Results:

  • Simulation experiments demonstrate the effectiveness of the proposed estimation methods.
  • The extended ETAS model with positive stable random effects significantly improved model fit for an east coast Taiwan earthquake sequence.
  • The positive stable random effects model outperformed both the original ETAS model and the gamma random effects variant.

Conclusions:

  • The extended ETAS model with random effects offers a more robust framework for seismic aftershock modeling.
  • The positive stable distribution is a promising choice for random effects in ETAS modeling, particularly for capturing complex seismic behavior.