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.

Statistical Seismology aims to bridge the gap between physics-based and statistics-based models. This volume provides a combination of reviews, methodological studies, and applications, which point to promising efforts in this field. The volume will be useful to students and professional researchers alike, who are interested in using stochastic modeling for probing the nature of earthquake phenomena, as well as an essential ingredient for earthquake forecasting.

This book addresses current activities in strong-motion networks around the globe, covering issues related to designing, maintaining and disseminating information from these arrays. The book is divided into three principal sections. The first section includes recent developments in regional and global ground-motion predictive models. It presents discussions on the similarities and differences of ground motion estimations from these models and their application to design spectra as well as other novel procedures for predicting engineering parameters in seismic regions with sparse data. The second section introduces topics about the particular methodologies being implemented in the recently established global and regional strong-motion databanks in Europe to maintain and disseminate the archived accelerometric data. The final section describes major strong-motion arrays around the world and their historical developments. The last three chapters of this section introduce projects carried out within the context of arrays deployed for seismic risk studies in metropolitan areas. Audience: This timely book will be of particular interest for researchers who use accelerometric data extensively to conduct studies in earthquake engineering and engineering seismology.

This book is the first comprehensive and methodologically rigorous analysis of earthquake occurrence. Models based on the theory of the stochastic multidimensional point processes are employed to approximate the earthquake occurrence pattern and evaluate its parameters. The Author shows that most of these parameters have universal values. These results help explain the classical earthquake distributions: Omori's law and the Gutenberg-Richter relation. The Author derives a new negative-binomial distribution for earthquake numbers, instead of the Poisson distribution, and then determines a fractal correlation dimension for spatial distributions of earthquake hypocenters. The book also investigates the disorientation of earthquake focal mechanisms and shows that it follows the rotational Cauchy distribution. These statistical and mathematical advances make it possible to produce quantitative forecasts of earthquake occurrence. In these forecasts earthquake rate in time, space, and focal mechanism orientation is evaluated.