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Bayesian Inference for Simulator Output

  • Thomas J. Santner
  • Brian J. Williams
  • William I. Notz
Chapter
Part of the Springer Series in Statistics book series (SSS)

Abstract

In Chap.  3 the correlation and precision parameters are completely unknown for the process model assumed to generate simulator output. In contrast this chapter assumes that the researcher has prior knowledge about the unknown parameters that is quantifiable in the form of a prior distribution.

References

  1. Andrieu C, Thoms J (2008) A tutorial on adaptive MCMC. Stat Comput 18(4): 343–373MathSciNetCrossRefGoogle Scholar
  2. Gelman A, Carlin J, Stern H, Dunson D, Vehtari A, Rubin D (2013) Bayesian data analysis. Chapman & Hall/CRC, Boca Raton, FLGoogle Scholar
  3. Graves TL (2011) Automatic step size selection in random walk Metropolis algorithms. Technical report LA-UR-11-01936, Los Alamos National Laboratory, Los Alamos, NMGoogle Scholar
  4. Haario H, Laine M, Mira A, Saksman E (2006) DRAM: efficient adaptive MCMC. Stat Comput 16(4):339–354MathSciNetCrossRefGoogle Scholar
  5. Handcock MS, Stein ML (1993) A Bayesian analysis of kriging. Technometrics 35:403–410CrossRefGoogle Scholar
  6. Jeffreys H (1961) Theory of probability. Oxford University Press, New York, NYzbMATHGoogle Scholar
  7. Montgomery GP, Truss LT (2001) Combining a statistical design of experiments with formability simulations to predict the formability of pockets in sheet metal parts. Technical report 2001-01-1130, Society of Automotive EngineersGoogle Scholar
  8. Oakley JE (2002) Eliciting Gaussian process priors for complex computer codes. Statistician 51:81–97MathSciNetGoogle Scholar
  9. Zimmerman DL, Cressie NA (1992) Mean squared prediction error in the spatial linear model with estimated covariance parameters. Ann Inst Stat Math 44:27–43MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Thomas J. Santner
    • 1
  • Brian J. Williams
    • 2
  • William I. Notz
    • 1
  1. 1.Department of StatisticsOhio State UniversityColumbusUSA
  2. 2.Statistical Sciences GroupLos Alamos National LaboratoryLos AlamosUSA

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