English

A cluster identification framework illustrated by a filtering model for earthquake occurrences

Statistics Theory 2009-06-12 v1 Statistics Theory

Abstract

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 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.

Keywords

Cite

@article{arxiv.0906.2099,
  title  = {A cluster identification framework illustrated by a filtering model for earthquake occurrences},
  author = {Zhengxiao Wu},
  journal= {arXiv preprint arXiv:0906.2099},
  year   = {2009}
}

Comments

Published in at http://dx.doi.org/10.3150/08-BEJ159 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

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