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Authors: Siino, Marianna* 
Adelfio, Giada* 
Title: Advanced spatio-temporal point processes for the Sicily seismicity analysis
Other Titles: Processi puntuali spatio-temporali avanzati per l’analisi della sismicità in Sicilia
Editors: Abbruzzo, Antonino 
Brentari, Eugenio 
Chiodi, Marcello 
Piacentino, Davide 
Issue Date: Jun-2018
Keywords: earthquakes
hybrid of Gibbs process
log-Gaussian Cox processes
minimum contrast method
non-separable covariance function
point process
spatio- temporal pair correlation function
Abstract: Due to the complexity of the generator process of seismic events, we study under several aspects the interaction structure between earthquake events using recently developed spatio-temporal statistical techniques and models. Using these advanced statistical tools, we aim to characterise the global and local scale cluster behaviour of the Easter Sicily seismicity considering the catalogue data since 2006, when the Italian National Seismic Network was upgraded and earthquake lo- cation was sensibly improved. Firstly, we characterise the global complex spatio- temporal interaction structure with the space-time ETAS model where background seismicity is estimated non-parametrically, while triggered seismicity is estimated by MLE. After identifying seismic sequences by a clustering technique, we charac- terise their spatial and spatio-temporal interaction structures using other advanced point process models. For the characterisation of the spatial interactions, a version of hybrid of Gibbs point process models is proposed as method to describe the multiscale interaction structure of several seismic sequences accounting for both the attractive and repulsive nature of data. Furthermore, we consider log-Gaussian Cox processes (LGCP), that are relatively tractable class of empirical models for describing spatio-temporal correlated phenomena. Several parametric formulation of spatio-temporal LGCP are estimated, by the minimum contrast procedure, assu- ming both separable and non-separable parametric specification of the correlation function of the underlying Gaussian Random Field.
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