Robust statistical methods to discriminate extreme events in geoelectrical precursory signals: Implications with earthquake prediction

In this study, we propose a robust statistical method to discern anomalous patterns in geoelectrical time series measured in a seismic area of the Southern Apennine chain. First, a filtering procedure to remove seasonal effects related to meteo-climatic fluctuations was carried out. Then, we selected an autoregressive model able to describe the time fluctuations of geoelectrical signals and propose a method to obtain an objective estimate of probability of occurrence for each extreme event detected in the time series. Our applications in Southern Italy allow us to hypothesize that the ambiguity of short-term prediction is within the complicated dynamics of the physical process responsible for electrical anomalies observed on the earth's surface.