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Reducing MCMC Computational Cost with a Two Layered Bayesian Approach

  • Conference paper
Model Validation and Uncertainty Quantification, Volume 3

Abstract

One of the major challenges in the implementation sampling techniques in the Bayesian approaches is the computational cost involved with the estimation of the likelihood and/or posterior, especially in problems where the models being updated are computationally expensive. This paper proposes the use of surrogate models in a two-layer Bayesian approach to reduce the computational cost of estimating these PDF. In the first layer, the posterior is written in a traditional manner. The second layer attempts to estimate the PDF of the first layer with a surrogate model. Only a few runs of the structural model are needed to create the required samples. Preliminary results are shown with a numerical example to identify the stiffness of a structural system. Only ten simulations of the structural model are used to estimate the posterior PDF.

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Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant No. CMMI-0846258.

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Authors and Affiliations

  1. University of South Carolina, 300 Main St., Columbia, SC, 29208, USA

    Ramin Madarshahian & Juan M. Caicedo

Authors
  1. Ramin Madarshahian
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  2. Juan M. Caicedo
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Corresponding author

Correspondence to Ramin Madarshahian .

Editor information

Editors and Affiliations

  1. Civil Engineering Department, Clemson University, Clemson, South Carolina, USA

    H. Sezer Atamturktur

  2. Department of Civil and Envt. Eng., Tufts University, Medford, Massachusetts, USA

    Babak Moaveni

  3. Department of Mechanical Engineering, University of Thessaly, Volos, Greece

    Costas Papadimitriou

  4. Sandia National Laboratories, Albuquerque, New Mexico, USA

    Tyler Schoenherr

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© 2015 The Society for Experimental Mechanics, Inc.

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Madarshahian, R., Caicedo, J.M. (2015). Reducing MCMC Computational Cost with a Two Layered Bayesian Approach. In: Atamturktur, H., Moaveni, B., Papadimitriou, C., Schoenherr, T. (eds) Model Validation and Uncertainty Quantification, Volume 3. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-15224-0_31

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  • DOI: https://doi.org/10.1007/978-3-319-15224-0_31

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15223-3

  • Online ISBN: 978-3-319-15224-0

  • eBook Packages: EngineeringEngineering (R0)

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