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Title: Hierarchical Bayesian Approach to Locating Seismic Events

Abstract

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).

Authors:
; ;
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
888581
Report Number(s):
UCRL-PROC-217057
TRN: US200618%%323
DOE Contract Number:
W-7405-ENG-48
Resource Type:
Conference
Resource Relation:
Conference: Presented at: 2005 Joint Statistical Meetings, Minneapolis, MN, United States, Aug 07 - Aug 11, 2005
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; EARTHQUAKES; EPICENTERS; DATA PROCESSING; MATHEMATICAL MODELS; MONTE CARLO METHOD

Citation Formats

Johannesson, G, Myers, S C, and Hanley, W G. Hierarchical Bayesian Approach to Locating Seismic Events. United States: N. p., 2005. Web.
Johannesson, G, Myers, S C, & Hanley, W G. Hierarchical Bayesian Approach to Locating Seismic Events. United States.
Johannesson, G, Myers, S C, and Hanley, W G. Wed . "Hierarchical Bayesian Approach to Locating Seismic Events". United States. doi:. https://www.osti.gov/servlets/purl/888581.
@article{osti_888581,
title = {Hierarchical Bayesian Approach to Locating Seismic Events},
author = {Johannesson, G and Myers, S C and Hanley, W G},
abstractNote = {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).},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Nov 09 00:00:00 EST 2005},
month = {Wed Nov 09 00:00:00 EST 2005}
}

Conference:
Other availability
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