Abstract
Stochastic models, wherein probability theory is employed for the estimation of the variables involved, are fundamental for modern seismological studies. The Gutenberg–Richter (G-R) law, the Poisson process, the Omori law and the Epidemic Type Aftershock Sequence (ETAS) models are stochastic and dominate modeling efforts. This chapter constitutes a detailed review on change point detection in seismicity modeling, combining both fundamental change point models and recent survey in the field. It comprises an introductory section to change point principles and presents detection techniques of the Poisson process, the ETAS model and the G-R law, as well as broader suggested approaches in seismicity rate changes that are employed in modern literature, covering parametric and non-parametric tests, as well as approaches lacking statistical hypothesis testing. ZMAP software has been developed for the detection of seismicity rate changes.
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