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Current Challenges in Statistical Seismology
English
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This§special issue emerged following the 2013 8th International Statistical§Seismology (StatSei8) workshop in Beijing. The articles within have been§collected to report on exciting new research in statistical seismology methods§and applications; it contains a collection of the newest methods, techniques§and results related to statistical analysis of earthquake occurrence and§earthquake probability forecasting. The articles within ultimately help to§define future research directions in the field. Especially, the rapid§development of observation technologies has brought geophysical research into§the big-data era. This includes not only non-seismicity geophysical data, such§as GPS observation on surface displacement, InSAR observation of the co-seismic§deformation, ionospheric observations, etc., but also extended seismological§data including slow earthquakes, tremor, and VLF earthquakes.§§The subject§of statistical seismology bridges the gap between physical and statistical§models. Many significant achievements have been accomplished during the last§several decades, including formulation of conditional intensity models for§quantifying seismicity rates, earthquake probability forecasts, and theories§related to rigorous testing of forecast models.§
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