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.
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A stochastic model is proposed for earthquake occurrences that considers the sequence of occurrences as composed of two parts: earthquake clusters and single earthquakes. We suggest that earthquake clusters contain a “mother quake” and her “offspring.” Applying the filtering techniques, we use the solution of filtering equations as criteria for declustering. A procedure for calculating maximum likelihood estimations (MLE’s) and the most likely cluster sequence is also presented.
Publié le : 2009-05-15
Classification:
earthquakes,
filtering,
Kushner–Stratonovich equations,
marked point process,
Zakai equations
@article{1241444894,
author = {Wu, Zhengxiao},
title = {A cluster identification framework illustrated by a filtering model for earthquake occurrences},
journal = {Bernoulli},
volume = {15},
number = {1},
year = {2009},
pages = { 357-379},
language = {en},
url = {http://dml.mathdoc.fr/item/1241444894}
}
Wu, Zhengxiao. A cluster identification framework illustrated by a filtering model for earthquake occurrences. Bernoulli, Tome 15 (2009) no. 1, pp. 357-379. http://gdmltest.u-ga.fr/item/1241444894/