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Bayesian Inference for Simulator Output

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The Design and Analysis of Computer Experiments

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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.

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Author information

Authors and Affiliations

  1. Department of Statistics, Ohio State University, Columbus, OH, USA

    Thomas J. Santner & William I. Notz

  2. Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM, USA

    Brian J. Williams

Authors
  1. Thomas J. Santner
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  2. Brian J. Williams
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  3. William I. Notz
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Santner, T.J., Williams, B.J., Notz, W.I. (2018). Bayesian Inference for Simulator Output. In: The Design and Analysis of Computer Experiments. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-8847-1_4

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