Mathematical principles of predicting the probabilities of large earthquakes

TL;DR

This paper develops a mathematical framework for predicting large earthquakes using a multicomponent random process, introducing tools for assessing prediction accuracy and testing predictor effectiveness.

Contribution

It presents a novel probabilistic model for earthquake prediction and introduces new methods for evaluating and testing prediction efficiency.

Findings

Established a model for space-time earthquake prediction

Developed tools for measuring prediction efficiency

Proposed a technique for testing predictor validity

Abstract

A multicomponent random process used as a model for the problem of space-time earthquake prediction; this allows us to develop consistent estimation for conditional probabilities of large earthquakes if the values of the predictor characterizing the seismicity prehistory are known. We introduce tools for assessing prediction efficiency, including a separate determination of efficiency for "time prediction" and "location prediction": a generalized correlation coefficient and the density of information gain. We suggest a technique for testing the predictor to decide whether the hypothesis of no prediction can be rejected.