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Analysis and Usage of Computer Experiments Using Spatial Linear Models  

Park, Jeong-Soo (Dept. of Statistics, Chonnam National University)
Publication Information
Abstract
One feature of a computer simulation experiment, different from a physical experiment, is that the output is often deterministic. Moreover the codes are computationally very expensive to run. This paper deals with the design and analysis of computer experiments(DACE) which is a relatively new statistical research area. We model the response of computer experiments as the realization of a stochastic process. This approach is basically the same as using a spatial linear model. Applications to the optimal mechanical designing and model calibration problems are illustrated. Algorithms for selecting the best spatial linear model are also proposed.
Keywords
Design and analysis of computer experiments; Kriging; Simulation code; Spatial linear model; Gaussian process; Calibration;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Park, J. S.(1994), 'Optimal Latin-hypercube designs for computer experiments', J. Stat. Plan Infer., Vol. 39, pp. 95-111   DOI   ScienceOn
2 Ryu, J. S., Kim, M. S., and Cha, K. J. et al.(2002), 'Kriging interpolation methods in geostatistics and DACE model', KSME Int Jour., Vol. 16, pp. 619-632
3 Welch, W. J., Buck, R. J., and Sacks, J. et al.(1992), 'Screening, predicting, and computer experiments', Technometrics, Vol. 34, pp. 15-25   DOI   ScienceOn
4 Kennedy, M. C. and O'Hagan, A.(2001), 'Bayesian calibration of computer models', J. Roy. Stat. Soc. B, Vol. 63, pp. 425-450   DOI   ScienceOn
5 Fang, K-T., Li, R., and Sudjianto, A.(2006), Design and Modeling for Computer Experiments, Chapman & Hall/CRC, Boca Raton
6 Kim, T. Y., Park, J. S., and Cox, D. D. (2002), 'Fast algorithm for cross-validation of the best linear unbiased predictor', Jour. Camp. Graph. Stat., Vol. 11, pp. 823-835   DOI   ScienceOn
7 Hertog, D. and Stehouwer, P.(2002). 'Optimizing color picture tube by high-cost nonlinear programming', European Journal of Operational Research, Vol. 140, pp. 197-211   DOI   ScienceOn
8 Sacks, J, Welch, W. J., Mitchell, T. et al.(1989), 'Design and analysis of computer experiments', Stat Sci., Vol. 4, pp. 409-435   DOI   ScienceOn
9 박정수, 황현식(2000), '라틴-하이퍼큐브 실험계혹 간의 거리 계산과 비교', '응용통계연구', 13권, 2호, pp. 477-488
10 심정욱, 박정수, 배종성(1994), 'Design and Analysis of Computer Experiments with applications to Quality Improvement', '응용통계연구', 7권, pp. 83-102
11 Santer, T. J., Williams, B. J., and Notz, W. I.(2003), The Design and Analysis of Computer Experiments, Springer, NY
12 Johnson, M., Moore, L., and Ylvisaker, D.(1990), 'Minimax and Maximin Distance Designs', Jour. Stat. Plan Infer., Vol. 26, pp. 131-148   DOI   ScienceOn
13 Park, J. S. and Jeon, J.(2002), 'Estimation of input parameters in complex simulation using a Gaussian process metamodel', Probabilistic Eng. Mech., Vol. 17, pp. 219-225   DOI   ScienceOn
14 Park, J. S. and Baek, J. S.(2001), 'Efficient computation of maximum likelihood estimators in a spatial linear model with power exponential covariogram', Comput Geosciences, Vol. 27, pp. 1-7   DOI   ScienceOn
15 Simpson, T. et al.(2001), 'Kriging models for global approximation in simulationbased multidisciplinary design optimization', AIAA Journal, Vol. 39, pp. 2233-2241   DOI   ScienceOn
16 Lim, Y. B., Sacks, J., and Studden, W.J. et al.(2002), 'Design and analysis of computer experiments when the output is highly correlated over the input space', Canad. J Stat., Vol. 30, pp. 109-126   DOI   ScienceOn
17 Lee, J. H.(1999), 'Asymptotic comparison of Latin hypercube sampling and its stratified version', Jour. Korean Stat. Soc, Vol. 28, pp. 135-150
18 Fang, K. T.(2002), 'Experimental designs for computer experiments and for industrial experiments with model unknown', Jour. Korean Stat. Soc., Vol. 30, pp. 277-300
19 Simpson, T. et al.(2001), 'Metamodels for computer-based engineering design: survey and recommendations', Engineering with Computers, Vol. 17, pp. 129-150   DOI   ScienceOn
20 Cox, D. D., Park, J. S., and Singer, C. E.(2001), 'A statistical method for tuning a computer code to a data base', Camp. Stat. Data Anal., Vol. 37, pp. 77-92   DOI   ScienceOn
21 Golub, G. H. and van Loan, C. F.(1996), Matrix Computations (3rd ed.), The Johns Hopkins University Press, Baltimore
22 Cox, D. D., Park, J. S., Singer, C. E., and Sacks, J.(1991), 'Tuning Complex computer Codes to Data', Proceedings 23rd Interface Conference, Vol. 23, pp. 266-271