Leveraging what you know: Versatile space-filling designs

References

• Anderson-Cook, C. M., and L. Lu. 2021. If you have it, Use It. Quality Progress 54 (4):52–5.
   Google Scholar
• Bowman, V. E., and D. C. Woods. 2013. Weighted space-filling designs. Journal of Simulation 7 (4):249–63. doi:10.1057/jos.2013.8.
   Web of Science ®Google Scholar
• Fang, K. T. 1980. The uniform design: Application of number-theoretic methods in experimental design. Acta Mathematicae Applicatae Sinica 3:363–72.
   Google Scholar
• Gramacy, R. B. 2020. Surrogates: Gaussian process modeling, design, and optimization for the applied sciences, Chapter 5. New York: Chapman & Hall/CRC Press.
   Google Scholar
• Gramacy, R. B., and H. K. H. Lee. 2008. Bayesian treed Gaussian process models with an application to computer modeling. Journal of the American Statistical Association 103 (483):1119–30. doi:10.1198/016214508000000689.
   Web of Science ®Google Scholar
• Gramacy, R. B., and H. K. H. Lee. 2009. Adaptive design and analysis of supercomputer experiments. Technometrics 51 (2):130–45. doi:10.1198/TECH.2009.0015.
   Google Scholar
• JMP® 2022. Version 17. Cary, NC: SAS Institute Inc.
   Google Scholar
• Johnson, M. E., L. M. Moore, and D. Ylvisaker. 1990. Minimax and maximin distance designs. Journal of Statistical Planning and Inference 26 (2):131–48. doi:10.1016/0378-3758(90)90122-B.
   Web of Science ®Google Scholar
• Joseph, R., T. Dasgupta, R. Tuo, and C. F. J. Wu. 2015. Sequential exploration of complex surfaces using minimum energy designs. Technometrics 57 (1):64–74. doi:10.1080/00401706.2014.881749.
   Web of Science ®Google Scholar
• Joseph, V. R. 2016. Space-filling designs for computer experiments: a review. Quality Engineering 28 (1):28–35. doi:10.1080/08982112.2015.1100447.
   Web of Science ®Google Scholar
• Joseph, V. R., and Y. Hung. 2008. Orthogonal-maximin Latin hypercube designs. Statistica Sinica 18:171–86.
   Web of Science ®Google Scholar
• Kyzyurova, K. N., J. O. Berger, and R. L. Wolpert. 2018. Coupling computer models through linking their statistical emulators. SIAM/ASA Journal on Uncertainty Quantification 6 (3):1151–71. doi:10.1137/17M1157702.
   Web of Science ®Google Scholar
• Lam, C. Q., and W. I. Notz. 2008. Sequential adaptive designs in computer experiments for response surface model fit. Statistics and Applications 6:207–33.
   Google Scholar
• Lekivetz, R., and B. Jones. 2015. Fast flexible space‐filling designs for nonrectangular regions. Quality and Reliability Engineering International 31 (5):829–37. doi:10.1002/qre.1640.
   Web of Science ®Google Scholar
• Lekivetz, R., and B. Jones. 2019. Fast flexible space‐filling designs with nominal factors for nonrectangular regions. Quality and Reliability Engineering International 35 (2):677–84. doi:10.1002/qre.2429.
   Web of Science ®Google Scholar
• Lewis, J. R., A. Zhang, and C. M. Anderson-Cook. 2018. Comparing multiple statistical methods for inverse prediction in nuclear forensic applications. Chemometrics and Intelligent Laboratory Systems 175:116–29. doi:10.1016/j.chemolab.2017.10.010.
   Web of Science ®Google Scholar
• Loeppky, J. L., L. M. Moore, and B. J. Williams. 2010. Batch sequential designs for computer experiments. Journal of Statistical Planning and Inference 140 (6):1452–64. doi:10.1016/j.jspi.2009.12.004.
   Web of Science ®Google Scholar
• Lu, L., and C. M. Anderson-Cook. 2021a. Input-response space-filling (IRSF) designs. Quality and Reliability Engineering International 37 (8):3529–51. doi:10.1002/qre.2931.
   Web of Science ®Google Scholar
• Lu, L., and C. M. Anderson-Cook. 2021b. Strategies for sequential design of experiments and augmentation. Quality and Reliability Engineering International 37 (5):1740–57. doi:10.1002/qre.2823.
   Web of Science ®Google Scholar
• Lu, L., C. M. Anderson-Cook, and T. Ahmed. 2021. Non-uniform space filling (NUSF) design. Journal of Quality Technology 53 (3):309–30. doi:10.1080/00224065.2020.1727801.
   Web of Science ®Google Scholar
• Lu, L., C. M. Anderson-Cook, M. Martin, and T. Ahmed. 2022. Practical choices for space filling designs. Quality and Reliability Engineering International 38 (3):1165–88. doi:10.1002/qre.2884.
   Web of Science ®Google Scholar
• Lu, L., C. M. Anderson-Cook, and T. J. Robinson. 2012. A case study to demonstrate Pareto frontiers for selecting a best response surface design while simultaneously optimizing multiple criteria. Applied Stochastic Models in Business and Industry 28 (3):206–21. doi:10.1002/asmb.940.
   Web of Science ®Google Scholar
• McKay, M., R. Beckman, and W. Conover. 1979. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 21 (2):239–45. doi:10.2307/1268522.
   Web of Science ®Google Scholar
• Morris, M., and T. Mitchell. 1995. Exploratory designs for computational experiments. Journal of Statistical Planning and Inference 43 (3):381–402. doi:10.1016/0378-3758(94)00035-T.
   Web of Science ®Google Scholar
• Myers, R. H., D. C. Montgomery, and C. M. Anderson-Cook. 2016. Response surface methodology: process and product optimization using designed experiments. 4th ed. New York: Wiley.
   Google Scholar
• Pronzato, L., and W. G. Muller. 2012. Design of computer experiments: space filling and beyond. Statistics and Computing 22 (3):681–701. doi:10.1007/s11222-011-9242-3.
   Web of Science ®Google Scholar
• Ranjan, P., D. Bingham, and G. Michailidis. 2008. Sequential experiment design for contour estimation from complex computer codes. Technometrics 50 (4):527–41. doi:10.1198/004017008000000541.
   Web of Science ®Google Scholar
• Santner, T. J., B. J. Williams, and W. I. Notz. 2003. The design and analysis of computer experiments. New York: Springer.
   Google Scholar