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Evaluation of ETAS and STEP Forecasting Models for California Seismicity Using Point Process Residuals

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  • Joshua Ward
  • Maximilian Werner
  • William Savran
  • Frederic Schoenberg

Abstract

Variants of the Epidemic‐Type Aftershock Sequence (ETAS) and Short‐Term Earthquake Probabilities (STEP) models have been used for earthquake forecasting and are entered as forecast models in the purely prospective Collaboratory Study for Earthquake Predictability (CSEP) experiment. Previous analyses have suggested the ETAS model offered the best forecast skill for the first several years of CSEP. Here, we evaluate the prospective forecasting ability of the ETAS and STEP one‐day forecast models for California from 2013 to 2017, using super‐thinned residuals and Voronoi residuals. We find very comparable performance of the two models, with slightly superior performance of the STEP model compared to ETAS according to most metrics.

Suggested Citation

  • Joshua Ward & Maximilian Werner & William Savran & Frederic Schoenberg, 2025. "Evaluation of ETAS and STEP Forecasting Models for California Seismicity Using Point Process Residuals," Environmetrics, John Wiley & Sons, Ltd., vol. 36(4), May.
    • Handle: RePEc:wly:envmet:v:36:y:2025:i:4:n:e70014
    DOI: 10.1002/env.70014
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    1. repec:bla:anzsta:v:46:y:2004:i:1:p:133-143 is not listed on IDEAS
    2. A. Baddeley & R. Turner & J. Møller & M. Hazelton, 2005. "Residual analysis for spatial point processes (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 617-666, November.
    3. Frederic Paik Schoenberg & Joshua Seth Gordon & Ryan J. Harrigan, 2018. "Analytic computation of nonparametric Marsan–Lengliné estimates for Hawkes point processes," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(3), pages 742-757, July.
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