A general dynamical cluster identification framework including both modeling and computation is developed.The earthquake declustering problem is studied to demonstrate how this framework applies.A stochastic model is proposed for earthquake occurrences that considers the sequence of occurrencesas composed of two parts: earthquake clusters and single earthquakes. We suggest that earthquake clusterscontain a “mother quake” and her “offspring.” Applying the filtering techniques, we use the solution offiltering equations as criteria for declustering. A procedure for calculating maximum likelihood estimations(MLE’s) and the most likely cluster sequence is also presented.
earthquakes, filtering, Kushner–Stratonovich equations, marked point process, Zakai equations
Geographic Information Sciences | Nature and Society Relations | Physical and Environmental Geography
Bernoulli Society for Mathematical Statistics and Probability
A cluster identification framework illustrated by a filtering model for earthquake occurrences. (2009). Bernoulli. 15, (2),. Research Collection School of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research_all/18
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