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Stochastic Kriging for Simulation Metamodeling

Stochastic Kriging for Simulation Metamodeling,10.1287/opre.1090.0754,Operations Research,B. Ankenman,B. L. Nelson,J. Staum

Stochastic Kriging for Simulation Metamodeling   (Citations: 6)
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Journal: Operations Research , vol. 58, no. 2, pp. 371-382, 2010
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    • ...We use stochastic kriging from Ankenman, Nelson, and Staum (2010) to produce the metamodel M. Stochastic kriging is an extension of kriging for deterministic computer experiments to stochastic simulation...

    Russell R. Bartonet al. A framework for input uncertainty analysis

    • ...(Yin, Ng, and Ng 2008) and (Ankenman, Nelson, and Staum 2010) propose the modified nugget effect model and the stochastic kriging model respectively to address the more general heteroscedastic case...
    • ...The general form of (1) is similar to the form proposed in (Ankenman, Nelson, and Staum 2010) when the defined intrinsic variance is estimated...
    • ...When Re is diagonal, (1) reduces to the independent noise model adopted by (Yin, Ng, and Ng 2008) and (Ankenman, Nelson, and Staum 2010)...

    Jun Yinet al. A Bayesian metamodeling approach for stochastic simulations

    • ...For the latter noise we refer to [2], [23], and [32]...

    Jack P. C. Kleijnenet al. Expected improvement in efficient global optimization through bootstra...

    • ...We use stochastic kriging (Ankenman, Nelson, and Staum 2010), but our procedure works with many metamodeling techniques...

    Ming Liuet al. Simulation on demand for pricing many securities

    • ...The purpose of this paper is to undertake a similar analysis of the interaction of CRN and a new metamodeling technique called stochastic kriging (Ankenman, Nelson, and Staum 2008, 2010)...
    • ...Ankenman, Nelson, and Staum (2010) used a two-point problem with all parameters known to show that CRN increases the mean squared error (MSE) of the MSE-optimal predictor at a prediction point that has equal extrinsic spatial correlation with the two design points...
    • ...We then extend the result given in Appendix A.2 in Ankenman, Nelson, and Staum (2010) for k ≥ 2 spatially uncorrelated design points and show that CRN inflates the MSE of prediction...
    • ...We assume that the trend parameters are unknown whereas Ankenman, Nelson, and Staum (2010) assumed that all parameters are known...
    • ...In this section we briefly review stochastic kriging as developed in Ankenman, Nelson, and Staum (2010) and the particular simplifications we exploit in this paper...
    • ...Further, if the variance of the noise depends on x, then complicated experiment design techniques (e.g., as developed in Ankenman, Nelson, and Staum 2010) are needed to properly counteract the effects of the non-constant variance...
    • ...For estimation of all of the parameters see Ankenman, Nelson, and Staum (2010)...

    Xi Chenet al. Common random numbers and stochastic kriging

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