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Stochastic earthquake interevent time modeling from exponentiated Weibull distributions

机译:随机地震挖掘时间造型从指数威布尔分布

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摘要

In view of the growing importance of stochastic earthquake modeling in disaster preparation, the present study introduces a new family of exponentiated Weibull distribution and examines its performance in earthquake interevent time analysis in a stationary point process. This three-parameter (one scale and two shapes) distribution not only covers the Weibull distribution, exponentiated exponential distribution, Burr-type X distribution, Rayleigh distribution, and exponential distribution as special sub-families, but also offers monotone and non-monotone hazard shapes. Here we first describe some of the exponentiated Weibull distribution properties, such as the survival rate, mode, median, and hazard rate. We then provide statistical inference and goodness-of-fit measures to examine the suitability of exponentiated Weibull model in comparison with other popular models, like exponential, gamma, lognormal, Weibull, and exponentiated exponential. Finally, we conduct real data analysis to assess the usefulness and flexibility of exponentiated Weibull distribution in the context of seismic interevent time modeling and associated applications. Results suggest that the exponentiated Weibull distribution has a comparable performance with other popular distributions of its nature. However, further investigations are necessary to confirm the importance and flexibility of exponentiated Weibull distribution in statistical seismology.
机译:鉴于随机地震建模在灾害制造中越来越重要,本研究介绍了一个新的指数威布尔分布系列,并在静止点过程中检查了地震发生的地震疏散时间分析。这三个参数(一种规模和两个形状)分布不仅涵盖了Weibull分布,指数指数分布,Burr-Type X分布,瑞利分布和指数分布为特殊子家庭,还提供单调和非单调的危险形状。在这里,我们首先描述一些指数的Weibull分布属性,例如生存率,模式,中位数和危险率。然后,我们提供统计推断和拟合措施,以检查指数威布尔模型的适用性与其他流行模型相比,如指数,伽玛,逻辑,威布尔和指数指数。最后,我们进行真实的数据分析,以评估在地震默认时间建模和相关应用程序的上下文中指数威布尔分布的有用性和灵活性。结果表明,指数化的Weibull分布具有与其性质的其他流行分布相当的性能。但是,需要进一步调查来确认指数威布尔分布在统计地震学中的重要性和灵活性。

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