| 摘要(英) |
To evaluate the risk of aftershock immediately after a strong earthquake for emergency rescue, the Reasenberg-Jones(RJ) model is conventionally employed, which assumes that the occurrence time and magnitude of aftershocks are independent, In practice, the longer it is after a major earthquake, the smaller the chance of a strong aftershock. Hence, Chen et al.(2015) proposed a modified RJ model, called MRJ, that allows the dependence between the time and magnitude. This thesis employs Bayesian analysis to analyze the MRJ model for the aftershock sequence after a M_L7.3, Taiwan, Chichi earthquake in 1999. There are two versions two kinds of Bayesian analysis, one is the traditional Bayesian analysis which is done when the prior distribution of the parameters in MRJ model is given from related historic earthquakes, the other is sequentially adjusted the prior distribution take previous distributions, called the sequentially updated Bayesian method. The two different Bayesian methods are need to evaluate the risk of above chi-chi aftershocks with magnitude at least 5. |
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