Clustering Analysis of Seismicity and Aftershock Identification
- Department of Mathematics and Statistics, University of Nevada, Reno, Nevada 89557-0084 (United States)
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)] based on the space-time-magnitude nearest-neighbor distance {eta} between earthquakes. We show that for a homogeneous Poisson marked point field with exponential marks, the distance {eta} has the Weibull distribution, which bridges our results with classical correlation analysis for point fields. The joint 2D distribution of spatial and temporal components of {eta} is used to identify the clustered part of a point field. The proposed technique is applied to several seismicity models and to the observed seismicity of southern California.
- OSTI ID:
- 21134099
- Journal Information:
- Physical Review Letters, Vol. 101, Issue 1; Other Information: DOI: 10.1103/PhysRevLett.101.018501; (c) 2008 The American Physical Society; Country of input: International Atomic Energy Agency (IAEA); ISSN 0031-9007
- Country of Publication:
- United States
- Language:
- English
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