A bayesian analysis for the seismic data on Taiwan

Tsai Hung Fan, Eng Nan Kuo

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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.

Original languageEnglish
Pages (from-to)599-609
Number of pages11
JournalAnnals of the Institute of Statistical Mathematics
Issue number4
StatePublished - Dec 2004


  • Conditional intensity function
  • Epidemic model
  • Hyperparameter
  • MCMC method
  • Prior distribution


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