Abstract
It is understood that sample size could be an issue in earthquake statistical studies, causing the best estimate being too deterministic or less representative derived from limited statistics from observation. Like many Bayesian analyses and estimates, this study shows another novel application of the Bayesian approach to earthquake engineering, using prior data to help compensate the limited observation for the target problem to estimate the magnitude of the recurring Meishan earthquake in central Taiwan. With the Bayesian algorithms developed, the Bayesian analysis suggests that the next major event induced by the Meishan fault in central Taiwan should be in Mw 6.44±0.33, based on one magnitude observation of Mw 6.4 from the last event, along with the prior data including fault length of 14km, rupture width of 15km, rupture area of 216km2, average displacement of 0.7m, slip rate of 6mm/yr, and five earthquake empirical models.
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