6533b7d3fe1ef96bd12600bb
RESEARCH PRODUCT
An algorithm for earthquakes clustering based on maximum likelihood
Dario LuzioMarcello ChiodiGiada Adelfiosubject
business.industryPattern recognitionMaximum likelihood sequence estimationPoisson distributionPoint processPhysics::Geophysicssymbols.namesakeCURE data clustering algorithmsymbolsETAS model earthquakes point process clusteringArtificial intelligenceSettore SECS-S/01 - Statisticaclustering earthquakesCluster analysisLikelihood functionbusinessAlgorithmPoint processes conditional intensity function likelihood function clustering methodRealization (probability)k-medians clusteringMathematicsdescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2007-01-01 |