Hierarchical Bayesian Approach to Locating Seismic Events

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We propose a hierarchical Bayesian model for conducting inference on the location of multiple seismic events (earthquakes) given data on the arrival of various seismic phases to sensor locations. The model explicitly accounts for the uncertainty associated with a theoretical seismic-wave travel-time model used along with the uncertainty of the arrival data. Posterior inferences is carried out using Markov chain Monte Carlo (MCMC).

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Johannesson, G; Myers, S C & Hanley, W G November 9, 2005.

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We propose a hierarchical Bayesian model for conducting inference on the location of multiple seismic events (earthquakes) given data on the arrival of various seismic phases to sensor locations. The model explicitly accounts for the uncertainty associated with a theoretical seismic-wave travel-time model used along with the uncertainty of the arrival data. Posterior inferences is carried out using Markov chain Monte Carlo (MCMC).

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  • Presented at: 2005 Joint Statistical Meetings, Minneapolis, MN, United States, Aug 07 - Aug 11, 2005

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  • Report No.: UCRL-PROC-217057
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 888581
  • Archival Resource Key: ark:/67531/metadc885270

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  • November 9, 2005

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  • Sept. 21, 2016, 2:29 a.m.

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  • Nov. 28, 2016, 9:27 p.m.

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Johannesson, G; Myers, S C & Hanley, W G. Hierarchical Bayesian Approach to Locating Seismic Events, article, November 9, 2005; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc885270/: accessed August 21, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.