Bayesian Analysis of Seismic Events

Abstract

Earthquakes are natural disasters that can have some of the most destructive impacts on society and the environment. Also, due to the shaking of the surface of the Earth that results from sudden release of energy in the Earth lithosphere, earthquakes can trigger other natural disasters, such as volcanic eruptions, landslides, avalanches, tsunamis, and floods. The earthquake‐generation process is a complex phenomenon that manifests as nonlinear dynamics in a wide array of spatial, temporal, and size scales, which range from centimeters to thousands of kilometers, from seconds to many thousands of years, and from weak events that cannot be perceived by the population to those with a violence that wreaks destruction across entire cities. In addition, the details of the space–time dynamics are not observable, and for most events, it is just the time, location, and proxy measures of the released energy that are recorded in catalogs which show increasing quality from the historical to the recent instrumental ones. In this context, Bayesian statistics is particularly suitable to incorporate statistical uncertainty associated with parameter estimation, in addition to the inherent uncertainty that is associated with the randomness of earthquake occurrences. With the development of new computational tools in recent years, the number of applications of Bayesian statistics in seismology has increased, even if many of them do not follow fully subjective approach, but rather those defined as frequentist‐Bayes and quasi‐Bayes approaches.