Reconciling data using Markov Chain Monte Carlo: An application to the Yellow Sea - Korean Peninsula region

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In an effort to build seismic models that are most consistent with multiple data sets, we have applied a new probabilistic inverse technique. This method uses a Markov Chain Monte Carlo (MCMC) algorithm to sample models from a prior distribution and test them against multiple data types to generate a posterior distribution. While computationally expensive, this approach has several advantages over a single deterministic model, notably the reconciliation of different data types that constrain the model, the proper handling of uncertainties, and the ability to include prior information. We also benefit from the advantage of forward modeling rather than inverting ... continued below

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Pasyanos, M E; Franz, G A & Ramirez, A L August 30, 2004.

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In an effort to build seismic models that are most consistent with multiple data sets, we have applied a new probabilistic inverse technique. This method uses a Markov Chain Monte Carlo (MCMC) algorithm to sample models from a prior distribution and test them against multiple data types to generate a posterior distribution. While computationally expensive, this approach has several advantages over a single deterministic model, notably the reconciliation of different data types that constrain the model, the proper handling of uncertainties, and the ability to include prior information. We also benefit from the advantage of forward modeling rather than inverting the data. Here, we use this method to determine the crust and upper mantle structure of the Yellow Sea and Korean Peninsula (YSKP) region. We discuss the data sets, parameterization and starting model, outline the technique and its implementation, observe the behavior of the inversion, and demonstrate some of the advantages of this approach.

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PDF-file: 12 pages; size: 2.4 Mbytes

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  • Journal Name: Journal of Geophysical Research; Journal Volume: 111

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  • Report No.: UCRL-JRNL-206357
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 883754
  • Archival Resource Key: ark:/67531/metadc891950

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  • August 30, 2004

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  • Sept. 23, 2016, 2:42 p.m.

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  • Dec. 1, 2016, 1:42 p.m.

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Pasyanos, M E; Franz, G A & Ramirez, A L. Reconciling data using Markov Chain Monte Carlo: An application to the Yellow Sea - Korean Peninsula region, article, August 30, 2004; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc891950/: accessed November 22, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.