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AGU: Journal of Geophysical Research, Solid Earth

 

Keywords

  • hidden Markov model
  • earthquake declustering
  • earthquake modeling

Index Terms

  • Mathematical Geophysics: Stochastic processes
  • Seismology: Earthquake dynamics
  • Seismology: Volcano seismology
Abstract
Cited By (1)
 

Abstract

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 115, B03306, 11 PP., 2010
doi:10.1029/2008JB005997

A hidden Markov model for earthquake declustering

Zhengxiao Wu

Department of Statistics and Applied Probability, National University of Singapore, Singapore

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.

Received 8 August 2009; accepted 9 November 2009; published 12 March 2010.

Citation: Wu, Z. (2010), A hidden Markov model for earthquake declustering, J. Geophys. Res., 115, B03306, doi:10.1029/2008JB005997.

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