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Bootstrapping and Conditional Simulation in Kriging: Better Confidence Intervals and Optimization

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Author Info

  • Mehdad, E.
  • Kleijnen, Jack P.C.

    (Tilburg University, Center for Economic Research)

Abstract

Abstract: This paper investigates two related questions: (1) How to derive a confidence interval for the output of a combination of simulation inputs not yet simulated? (2) How to select the next combination to be simulated when searching for the optimal combination? To answer these questions, the paper uses parametric bootstrapped Kriging and "conditional simulation". Classic Kriging estimates the variance of its predictor by plugging-in the estimated GP parameters so this variance is biased. The main conclusion is that classic Kriging seems quite robust; i.e., classic Kriging gives acceptable confidence intervals and estimates of the optimal solution.

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Bibliographic Info

Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2013-038.

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Date of creation: 2013
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Handle: RePEc:dgr:kubcen:2013038

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Web page: http://center.uvt.nl

Related research

Keywords: Simulation; Optimization; Kriging; Bootstrap;

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References

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  1. Kleijnen, J.P.C., 2008. "Review of the book [Design and Analysis of Simulation Experiments]," Open Access publications from Tilburg University urn:nbn:nl:ui:12-4379049, Tilburg University.
  2. Kleijnen, J.P.C., 2007. "Kriging Metamodeling in Simulation: A Review," Discussion Paper 2007-13, Tilburg University, Center for Economic Research.
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Cited by:
  1. Kleijnen, Jack P.C., 2013. "Simulation-Optimization via Kriging and Bootstrapping: A Survey (Revision of CentER DP 2011-064)," Discussion Paper 2013-064, Tilburg University, Center for Economic Research.

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