2008
DOI: 10.1103/physrevlett.101.018501
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Clustering Analysis of Seismicity and Aftershock Identification

Abstract: We introduce a statistical methodology for clustering analysis of seismicity in the time-space-energy domain and use it to establish the existence of two statistically distinct populations of earthquakes: clustered and nonclustered. This result can be used, in particular, for nonparametric aftershock identification. The proposed approach expands the analysis of Baiesi and Paczuski [Phys. Rev. E 69, 066106 (2004)10.1103/PhysRevE.69.066106] based on the space-time-magnitude nearest-neighbor distance eta between … Show more

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Cited by 317 publications
(350 citation statements)
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References 16 publications
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“…As it was shown in Zaliapin and Ben-Zion (2013a), Zaliapin et al (2008) and Zaliapin and Ben-Zion (2015), earthquake catalogues show a bimodal joint distribution of ðlog 10 T; log 10 RÞ. One mode corresponds to the background events-like events in a Poisson process-while the other corresponds to the clustered events with n ij \10 À5 , i.e.…”
Section: Second Methodsmentioning
confidence: 98%
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“…As it was shown in Zaliapin and Ben-Zion (2013a), Zaliapin et al (2008) and Zaliapin and Ben-Zion (2015), earthquake catalogues show a bimodal joint distribution of ðlog 10 T; log 10 RÞ. One mode corresponds to the background events-like events in a Poisson process-while the other corresponds to the clustered events with n ij \10 À5 , i.e.…”
Section: Second Methodsmentioning
confidence: 98%
“…One mode corresponds to the background events-like events in a Poisson process-while the other corresponds to the clustered events with n ij \10 À5 , i.e. events closer in time and space to their parents than expected in a Poisson process Ben-Zion 2013a, 2015;Zaliapin et al 2008). Figure 6 depicts this bimodal distribution for the Global CMT catalogue.…”
Section: Second Methodsmentioning
confidence: 99%
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