Publication Type

Journal Article

Publication Date

3-2010

Abstract

The hidden Markov model (HMM) and related algorithms provide a powerful framework for statistical inference on partially observed stochastic processes. HMMs have been successfully implemented in many disciplines, though not as widely applied as they should be in earthquake modeling. In this article, a simple HMM earthquake occurrence model is proposed. Its performance in declustering is compared with the epidemic-type aftershock sequence model, using a data set of the central and western regions of Japan. The earthquake clusters and the single earthquakes separated using our model show some interesting geophysical differences. In particular, the log-linear Gutenberg-Richter frequency-magnitude law (G-R law) for the earthquake clusters is significantly different from that for the single earthquakes.

Discipline

Geographic Information Sciences | Nature and Society Relations

Research Areas

Economic Theory

Publication

Journal of Geophysical Research

Volume

115

Issue

B3

ISSN

0148-0227

Identifier

10.1029/2008JB005997

Publisher

American Geophysical Union (AGU) / Wiley

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org./10.1029/2008JB005997

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