Aftershock identification problem via the nearest-neighbor analysis for marked point processes
Abstract
The centennial observations on the world seismicity have revealed a wide variety of clustering phenomena that unfold in the space-time-energy domain and provide most reliable information about the earthquake dynamics. However, there is neither a unifying theory nor a convenient statistical apparatus that would naturally account for the different types of seismic clustering. In this talk we present a theoretical framework for nearest-neighbor analysis of marked processes and obtain new results on hierarchical approach to studying seismic clustering introduced by Baiesi and Paczuski (2004). Recall that under this approach one defines an asymmetric distance D in space-time-energy domain such that the nearest-neighbor spanning graph with respect to D becomes a time- oriented tree. We demonstrate how this approach can be used to detect earthquake clustering. We apply our analysis to the observed seismicity of California and synthetic catalogs from ETAS model and show that the earthquake clustering part is statistically different from the homogeneous part. This finding may serve as a basis for an objective aftershock identification procedure.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2007
- Bibcode:
- 2007AGUFMNG31A..04G
- Keywords:
-
- 3235 Persistence;
- memory;
- correlations;
- clustering (3265;
- 7857);
- 3252 Spatial analysis (0500);
- 3265 Stochastic processes (3235;
- 4468;
- 4475;
- 7857);
- 7209 Earthquake dynamics (1242);
- 7223 Earthquake interaction;
- forecasting;
- and prediction (1217;
- 1242)