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Gutenberg–Richter B-Value Time Series Forecasting: A Weighted Likelihood Approach

Author

Listed:
  • Matteo Taroni

    (Istituto Nazionale di Geofisica e Vulcanologia, Via di Vigna Murata 605, 00143 Rome, Italy)

  • Giorgio Vocalelli

    (Department of Economics and Finance, Tor Vergata University of Rome, Via Columbia 2, 00133 Rome, Italy)

  • Andrea De Polis

    (Warwick Business School, University of Warwick, Scarman Rd, Coventry CV4 7AL, UK)

Abstract

We introduce a novel approach to estimate the temporal variation of the b-value parameter of the Gutenberg–Richter law, based on the weighted likelihood approach. This methodology allows estimating the b-value based on the full history of the available data, within a data-driven setting. We test this methodology against the classical “rolling window” approach using a high-definition Italian seismic catalogue as well as a global catalogue of high magnitudes. The weighted likelihood approach outperforms competing methods, and measures the optimal amount of past information relevant to the estimation.

Suggested Citation

  • Matteo Taroni & Giorgio Vocalelli & Andrea De Polis, 2021. "Gutenberg–Richter B-Value Time Series Forecasting: A Weighted Likelihood Approach," Forecasting, MDPI, vol. 3(3), pages 1-9, August.
    • Handle: RePEc:gam:jforec:v:3:y:2021:i:3:p:35-569:d:609430
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    References listed on IDEAS

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    1. Danijel Schorlemmer & Stefan Wiemer & Max Wyss, 2005. "Variations in earthquake-size distribution across different stress regimes," Nature, Nature, vol. 437(7058), pages 539-542, September.
    2. Laura Gulia & Stefan Wiemer, 2019. "Real-time discrimination of earthquake foreshocks and aftershocks," Nature, Nature, vol. 574(7777), pages 193-199, October.
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