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Earthquakes occurrences estimation through a parametric semi-Markov approach

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  • Giovanni Masala

Abstract

The estimation of earthquakes’ occurrences prediction in seismic areas is a challenging problem in seismology and earthquake engineering. Indeed, the prevention and the quantification of possible damage provoked by destructive earthquakes are directly linked to this kind of prevision. In our paper, we adopt a parametric semi-Markov approach. This model assumes that a sequence of earthquakes is seen as a Markov process and besides it permits to take into consideration the more realistic assumption of events’ dependence in space and time. The elapsed time between two consecutive events is modeled as a general Weibull distribution. We determine then the transition probabilities and the so-called crossing states probabilities. We conclude then with a Monte Carlo simulation and the model is validated through a large database containing real data.

Suggested Citation

  • Giovanni Masala, 2012. "Earthquakes occurrences estimation through a parametric semi-Markov approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(1), pages 81-96, March.
    • Handle: RePEc:taf:japsta:v:39:y:2012:i:1:p:81-96
    DOI: 10.1080/02664763.2011.578617
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    Cited by:

    1. Votsi, I. & Limnios, N. & Tsaklidis, G. & Papadimitriou, E., 2013. "Hidden Markov models revealing the stress field underlying the earthquake generation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(13), pages 2868-2885.
    2. Danisman, Ozgur & Uzunoglu Kocer, Umay, 2021. "Hidden Markov models with binary dependence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).

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