- ๚๖(Date)
- 2012N1025๚iุj/ 25 Oct 2012 (Thursday)

- ๊

(Location) - vค 4KEW /

4F lounge @ Institute of Statistical Mathematics

- ิ(Time)
- 16F00`

- uา

(Speaker) - ฿]G (ๅw JST) /

Takahiro Omi (JST, the University of Tokyo)

- uฺ่

(Title) - A state-space model for estimating the time-varying detection rate of earthquakes and its application to immediate probabilistic prediction of aftershocks.

- Tv

(Abstract) -
After a large earthquake, the detection rate of earthquakes temporarily decreases, and a lot of earthquakes are missed from a catalog. Such incompleteness of the catalog prevents us from estimating statistical models of aftershock activity accurately. To overcome this difficulty, Ogata and Katsura (2005) modeled the incomplete catalog by using a parametric model of a time-varying detection rate of earthquakes.

In this talk, we propose a state space model for estimating the time- varying detection rate. In our model, the estimation problem is recursively solved, by using Kalman filter and a Gaussian approximation of the posterior probability distribution. Thus our model has an advantage in real-time computation. Finally our model is combined with the Omori-Utsu law to predict the occurrence rate of underlying aftershocks. We present some results on the immediate probabilistic prediction of aftershocks.