Statistical Tests for Cross-Validation of Kriging Models
Published Online:31 Aug 2021https://doi.org/10.1287/ijoc.2021.1072
References
- (2017) Cross-validation estimation of covariance parameters under fixed-domain asymptotics. J. Multivariate Anal. 160:42–67.Crossref, Google Scholar
- (2009) Diagnostics for Gaussian process emulators. Technometrics 51(4):425–438.Crossref, Google Scholar
- (2018) Kriging modeling to predict viscosity index of base oils. Energy Fuels 32(2):2588–2597.Crossref, Google Scholar
- (2006) The correct Kriging variance estimated by bootstrapping. J. Oper. Res. Soc. 57(4):400–409.Crossref, Google Scholar
- (2015) Frequentist accuracy of Bayesian estimates. Royal Statist. Soc. Ser. B 77(3):617–646.Crossref, Google Scholar
- (2018) Comparison of Gaussian process modeling software. Eur. J. Oper. Res. 266(1):179–192.Crossref, Google Scholar
- (2010) Multiobjective global surrogate modeling, dealing with the 5-percent problem. Engrg. Comput. 26:81–98.Crossref, Google Scholar
- (2016) laGP: large-scale spatial modeling via local approximate Gaussian processes in R. J. Statist. Software 72(1):1–46.Crossref, Google Scholar
- (2015) Local Gaussian process approximation for large computer experiments. J. Comput. Graphical Statist. 24(2):561–578.Crossref, Google Scholar
- (2020) Online risk monitoring using online simulation. INFORMS J. Comput. 32(2):356–375.Abstract, Google Scholar
- (1983) Cross-validation using the t statistic. Eur. J. Oper. Res. 13(2):133–141.Crossref, Google Scholar
- (2015) Design and Analysis of Simulation Experiments, 2nd ed. (Springer, New York).Crossref, Google Scholar
- (2017) Design and analysis of simulation experiments: Tutorial. Tolk A, Fowler J, Shao G, Yucesan E, eds. Advances in Modeling and Simulation: Seminal Research from 50 Years of Winter Simulation Conferences (Springer, New York), 135–158.Crossref, Google Scholar
- (2020) Prediction for big data through Kriging: Small sequential and one-shot designs. Amer. J. Math. Management Sci. 39(3):199–213.Google Scholar
- (2015) UQLab user manual–Kriging (Gaussian process modelling). Report UQLab-V0.9-105, Chair of Risk, Safety & Uncertainty Quantification, ETH Zurich, Zurich, Switzerland.Google Scholar
- (2019) Virtual statistics in simulation via k nearest neighbors. INFORMS J. Comput. 31(3):576–592.Link, Google Scholar
- (2009) Choosing the sample size of a computer experiment: A practical guide. Technometrics 51(4):366–376.Crossref, Google Scholar
- (2002) DACE: A Matlab Kriging Toolbox, Version 2.0 (IMM Technical University of Denmark, Kongens Lyngby, Denmark).Google Scholar
- (2015) Classic Kriging vs. Kriging with bootstrapping or conditional simulation: Classic Kriging’s robust confidence intervals and optimization. J. Oper. Res. Soc. 66(11):1804–1814.Crossref, Google Scholar
- (2018) Kriging-assisted robust black-box simulation optimization in direct speed control of DC motor under uncertainty. IEEE Trans. Magn. 54(7):1–10.Crossref, Google Scholar
- (2001) On the effect of covariance function estimation on the accuracy of kriging predictors. Bernoulli 7(3):421–438.Crossref, Google Scholar
- (2006) Gaussian Processes for Machine Learning (MIT Press, Cambridge, MA).Google Scholar
- (2011) Power comparisons of Shapiro–Wilk, Kolmogorov–Smirnov, Lilliefors and Anderson–Darling tests. J. Statist. Modeling Analytics 2(1):21–33.Google Scholar
- (2012) DiceKriging, DiceOptim: Two R packages for the analysis of computer experiments by Kriging-based metamodeling and optimization. J. Statist. Software 51(1):1–55.Crossref, Google Scholar
- (2019) Generalized integrated Brownian fields for simulation metamodeling. Oper. Res. 67(3):874–891.Link, Google Scholar
- (2018) The Design and Analysis of Computer Experiments, 2nd revised ed. (Springer, New York).Crossref, Google Scholar
- (1986) An improved Bonferroni procedure for multiple tests of significance. Biometrika 73(3):751–754.Crossref, Google Scholar
- (2018) Emulating satellite drag from large simulation experiments. J. Uncertainty Quantification 7(2):720–759.Crossref, Google Scholar
- (2018) Using history matching for prior choice. Technometrics 60(4):445–460.Crossref, Google Scholar
- (2021) Distance-distributed design for Gaussian process surrogates. Technometrics 63(1):40–52.Crossref, Google Scholar
- (2021) Stochastic Kriging for inadequate simulation models. https://arxiv.org/pdf/1802.00677v1.pdf.Google Scholar

