References
- 김윤태, 고 원, 박혜련, '분석용 정밀 워게임 모형의 통계적 진단 및 활용', 2004 한국통계학회 추계 학술대회 논문집, 117-121, 2004
- Barton, R. R., 'Metamodels for simulation input-output relations', Proceedings of the 1992 Winter Simulation Conference, 289-299, 1992
- McKay, M. D., Beckman, R. J., and Conover, W. J., 'A Comparison of three methods for selecting values of input variables in the analysis of output from a computer code', Technometrics, 21(2), 239-245, 1979 https://doi.org/10.2307/1268522
- Stein, M., 'Large sample properties of simulation using Latin hypercube sampling', Technometrics, 29, 143-151, 1987 https://doi.org/10.2307/1269769
- Sacks, J., Welch, W. J., Mitchell, T. J. and Wynn, H. P., 'Design and analysis of computer experiments', Statistical Science, 4(4), 409-435, 1989 https://doi.org/10.1214/ss/1177012413
- Shewry, M. and Wynn, H., 'Maximum entropy sampling', Journal of Applied Statistics, 14, 409-435, 1987
- Tang, B., 'Orthogonal array-based Latin hypercubes', Journal of the American Statistical Association, 88(424), 13921397, 1993
- Ye, K. Q., 'Orthogonal column latin hypercubes and their application in computer experiments', Journal of the American Statistical Association, 93(444), 1430-1439, 1998 https://doi.org/10.2307/2670057
- Owen, A. B., 'Controlling correlations in Latin hypercube samples', Journal of the American Statistical Association, 89(428), 1515-1522, 1994
- Tang, B., 'Selecting Latin hypercubes using correlation criteria', Statistica Sinica, 8, 965-977, 1998
- Morris, M. D., Mitchell, T. J., 'Exploratory designs for computational experiments', Journal of Statistical Planning and Inference, 43, 381-402, 1995 https://doi.org/10.1016/0378-3758(94)00035-T
- Joseph, V. R., Hung, Y., 'Orthogonalmaximin Latin hypercube designs', Statistica Sinica, to appear, 2006
- Lunani, M., Sudjianto, A., and Johnson, P. L., 'Generating efficient training samples for neural networks using Latin hypercube sampling', Intelligent Engineering Systems Through Artificial Neural Networks, 5, 209-214, 1995
- Alam, F. M., McNaught, K. R., and Ringrose, T. J., 'A comparison of experimental designs in the development of a neural network simulation metamodel', Simulation Modelling Practice and Theory, 12, 559-578, 2004 https://doi.org/10.1016/j.simpat.2003.10.006
- Simpson, T. W, Peplinski, J. D, Koch, P. N. and Allen, J. K., 'Metamodels for computer-based engineering design: Survey and recommendations', Engineering with Computers, 17, 129-150, 2001 https://doi.org/10.1007/PL00007198
- Allen, T. T., Kabiri-Bemshteyn, K., and Bamoradian, K. K, 'Constructing metamodels for computer experiments', Journal of Quality Technology, 35(3), 264-274, 2003 https://doi.org/10.1080/00224065.2003.11980220
- Davis, P. K., Bigelow, J. H., Motivated Metamodels, RAND, Santa Monica, CA, 2004
- 문형곤, 윤직석, 유승근, 01 육군 전투실험기술 지원 연구보고서, 한국국방연구원, 2001
- Box, G. E. P., Wilson, K. B., 'On the experimental attainment of optimum conditions', Journal of the Royal Statistic Society Ser. B(Methodological), 13(1), 1-45, 1951
- Montgomery, D. C., Design and Analysis of Experiments, 6th. ed., Chapter 11, John Wiley & Sons Inc., New York, 2005
- SAS/STAT 9.1 User's Guide, 2004
- Phadke, M. S., Quality Engineering Using Robust Design, p.293, PTR Prentice-Hall, Inc., Englewood Cliffs, New Jersey, 1989
- MATLAB v.7.0.1 Manual, Backpropagation in Neural Network Toolbox, 2004