HR: 1340h
AN: S23A-0300 [Abstracts]
TI: Analyzing earthquake clustering features by stochastic reconstruction -- foreshocks
AU: * Zhuang, J
EM: zhuangjc@ism.ac.jp
AF: Institute of Statistical Mathematics, 4-6-7 Minami Azabu, Minato-Ku, Tokyo, 106-8569
Japan
AU: Ogata, Y
EM: ogata@ism.ac.jp
AF: Institute of Statistical Mathematics, 4-6-7 Minami Azabu, Minato-Ku, Tokyo, 106-8569
Japan
AB:
The ETAS model has been proved to be able to be used the first
approximation for describe the earthquake clustering features
(Zhuang et al 2004, JGR, 109, No. B5, B05301,
doi:10.1029/2003JB002879). This model classifies the seismicity
into two components, the background and the cluster, where each
earthquake event, no matter if it is from the background component
(usually assumed to be a space-time Poisson process, stationary or
non-stationary, homogeneous or non-homogeneous) or generated by
another event, produces (triggers) its own offspring (aftershocks)
according to some branching rules. Its conditional intensity
function at the space-time-magnitude location $(t, x, y, M)$, has
the form of
$$\lambda(t,x,y,M|\hit)=J(M)\left[\mu(x,y)+\sum_{i:t_i
DE: 7223 Seismic hazard assessment and prediction
DE: 7230 Seismicity and seismotectonics
DE: 7209 Earthquake dynamics and mechanics
DE: 3220 Nonlinear dynamics
SC: Seismology [S]
MN: 2004 AGU Fall Meeting