A Bayesian approach is used to analyze the seismic events with magnitudes at least 4.7 on Taiwan. Following the idea proposed by Ogata (1988, Journal of the American Statistical Association, 83, 9-27), an epidemic model for the process of occurrence times given the observed magnitude values is considered, incorporated with gamma prior distributions for the parameters in the model, while the hyper-parameters of the prior are essentially determined by the seismic data in an earlier period. Bayesian inference is made on the conditional intensity function via Markov chain Monte Carlo method. The results yield acceptable accuracies in predicting large earthquake events within short time periods.
|Number of pages||11|
|Journal||Annals of the Institute of Statistical Mathematics|
|State||Published - Dec 2004|
- Conditional intensity function
- Epidemic model
- MCMC method
- Prior distribution