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A Bayesian study of temporal changes in seismicity

Conference Paper
Publication Date:
2023
abstract:
The q-exponential distribution, solution of a maximum entropy problem in the frame of nonextensive statistical mechanics, is useful for describing complex, non-linear dynamic systems that emerge in many applications of environmental and social sciences, including seismology. In this study we analyze the seismic sequence of L'Aquila earthquake and investigate the ability of the q-exponential probability distribution to grasp the temporal variations of some seismic parameters, such as magnitude and spatial location of the epicentres. Bayesian inference is performed by processing data on sliding time windows, such that each window has a fixed number of events and shifts at each new event. Other distributions (tapered Pareto, generalized gamma) are also considered and the best fitting distribution in each time window is selected by comparing the evaluated values of the posterior marginal likelihood. We found that the best fitting distribution varies over time and can be a further indicator of the activation state of the systems.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
q-exponential distribution; Voronoi tessellations; Bayesian inference; Probabilistic forecasting; Statistical seismology
List of contributors:
Rotondi, Renata; Varini, Elisa
Authors of the University:
VARINI ELISA
Handle:
https://iris.cnr.it/handle/20.500.14243/456586
Book title:
Proceedings of the GRASPA 2023 Conference
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