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EnglishIn this paper we propose a clustering technique set up to separate and find out the two main components of seismicity: the background seismicity and the triggered one. We suppose that a seismic catalogue is the realization of a non homogeneous space-time Poisson clustered process, with a different parametrization for the intensity function of the Poisson-type component and of the clustered (triggered) component. The method here proposed assigns each earthquake to the cluster of earthquakes, or to the set of independent events, according to the increment to the likelihood function, computed using the conditional intensity function estimated by maximum likelihood methods and iteratively changing the assignment of the events; after a change of partition, MLE of parameters are estimated again and the process is iterated until there is no more improvement in the likelihood.
Adelfio, G., Chiodi, M., & Luzio, D. (2010). An Algorithm for Earthquakes Clustering based on Maximum Likelihood. In F. Palumbo, C.N. Lauro, & M.J. Greenacre (a cura di), Data Analysis and Classification - Proceedings of the 6th Conference of the Classification and Data Analysis Group of the Società Italiana di Statistica (pp. 25-32). Berlin : Springer.
| Data di pubblicazione: | 2010 | |
| Titolo: | An Algorithm for Earthquakes Clustering based on Maximum Likelihood | |
| Autori: | ||
| Citazione: | Adelfio, G., Chiodi, M., & Luzio, D. (2010). An Algorithm for Earthquakes Clustering based on Maximum Likelihood. In F. Palumbo, C.N. Lauro, & M.J. Greenacre (a cura di), Data Analysis and Classification - Proceedings of the 6th Conference of the Classification and Data Analysis Group of the Società Italiana di Statistica (pp. 25-32). Berlin : Springer. | |
| Abstract: | In this paper we propose a clustering technique set up to separate and find out the two main components of seismicity: the background seismicity and the triggered one. We suppose that a seismic catalogue is the realization of a non homogeneous space-time Poisson clustered process, with a different parametrization for the intensity function of the Poisson-type component and of the clustered (triggered) component. The method here proposed assigns each earthquake to the cluster of earthquakes, or to the set of independent events, according to the increment to the likelihood function, computed using the conditional intensity function estimated by maximum likelihood methods and iteratively changing the assignment of the events; after a change of partition, MLE of parameters are estimated again and the process is iterated until there is no more improvement in the likelihood. | |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1007/978-3-642-03739-9_3 | |
| Settore Scientifico Disciplinare: | Settore SECS-S/01 - Statistica | |
| Appare nelle tipologie: | 2.01 Capitolo o Saggio |
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