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Estimating the Variance of the Predictor in Stochastic Kriging

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  • Kleijnen, J.P.C.

    (Tilburg University, School of Economics and Management)

  • Mehdad, Ehsan

    (Tilburg University, School of Economics and Management)

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  • Kleijnen, J.P.C. & Mehdad, Ehsan, 2015. "Estimating the Variance of the Predictor in Stochastic Kriging," Other publications TiSEM dbbd2fa2-eccf-4f71-be9b-c, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:dbbd2fa2-eccf-4f71-be9b-cb15f9ebad30
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    References listed on IDEAS

    as
    1. Ehsan Mehdad & Jack P C Kleijnen, 2015. "Classic Kriging versus Kriging with bootstrapping or conditional simulation: classic Kriging’s robust confidence intervals and optimization," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(11), pages 1804-1814, November.
    2. Bruce Ankenman & Barry L. Nelson & Jeremy Staum, 2010. "Stochastic Kriging for Simulation Metamodeling," Operations Research, INFORMS, vol. 58(2), pages 371-382, April.
    3. Jack P.C. Kleijnen, 2015. "Design and Analysis of Simulation Experiments," International Series in Operations Research and Management Science, Springer, edition 2, number 978-3-319-18087-8, April.
    4. Russell R. Barton & Barry L. Nelson & Wei Xie, 2014. "Quantifying Input Uncertainty via Simulation Confidence Intervals," INFORMS Journal on Computing, INFORMS, vol. 26(1), pages 74-87, February.
    5. Roustant, Olivier & Ginsbourger, David & Deville, Yves, 2012. "DiceKriging, DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 51(i01).
    6. Lihua Sun & L. Jeff Hong & Zhaolin Hu, 2014. "Balancing Exploitation and Exploration in Discrete Optimization via Simulation Through a Gaussian Process-Based Search," Operations Research, INFORMS, vol. 62(6), pages 1416-1438, December.
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