List of Papers

Spring 2014 Talks

  1. Notz, W., “Into talk” (PDF , 228K, requires Adobe Acrobat Reader)

  2. Pratola, M., “Treed processes talk” (PDF , 1950K, requires Adobe Acrobat Reader)

  3. Davis, C., “Nonstationary Gaussian processes in computer experiments talk” (PDF , 693K, requires Adobe Acrobat Reader)

  4. Vaidyanathan, S., “Calibration” (PDF , 291K, requires Adobe Acrobat Reader)



Miscellaneous Papers

  1. Bursztyn, D., and Steinberg, D., “Comparison of designs for computer experiments,” Journal of Statistical Planning and Inference, Vol. 136, 2006, pp. 1103-1119. (PDF , 159K, requires Adobe Acrobat Reader)

  2. Chen, R-B., Hsieh, D-N., Hung, Y., and Wang, W., “Optimizing Latin hypercube designs by particle swarm,” Statistics and Computing, Vol. 23, 2013, pp. 663-676. (PDF , 794K, requires Adobe Acrobat Reader)

  3. Cherry, S., Banfield, J., and Quimby, W.F., “An Evaluation of a non-parametric method of estimating semi-variograms of isotropic spatial processes,” Journal of Applied Statistics, Vol. 23, No.4, 1996, pp. 435-449. (PDF , 213K, requires Adobe Acrobat Reader)

  4. Conti, S., Gosling, J. P., Oakley, J. E., and O'Hagan, A. “Gaussian process emulation of dynamic computer codes,” Biometrika, Vol. 96, 2009, pp. 663-676. (PDF , 314K, requires Adobe Acrobat Reader)

  5. Drignei, D. and Morris, M. D. “Empirical Bayesian Analysis for Computer Experiments Involving Finite-Difference Codes,” JASA, Vol. 101, 2006, pp. 1527-1536. (PDF , 501K, requires Adobe Acrobat Reader)

  6. Hall, P.,Fisher, N., and Hoffman, B., “On the Nonparametric Estimation of Covariance Functions,” The Annals of Statistics, Vol. 22, No. 4, 1994, pp. 2115-2134. (PDF , 1440K, requires Adobe Acrobat Reader)

  7. Hankin, R., “Introducing BACCO, an R Bundle for Bayesian Analysis of Computer Code Output,” Journal of STatistical Software, Issue 16, 2005. (PDF , 676K, requires Adobe Acrobat Reader)

  8. Jones, B. and Johnson, R. T., “Design and Analysis for the Gaussian Process Model (with discussion),” Qual. Reliab. Eng. Int., Vol. 25, 2009, pp. 515-524. (PDF , 407K, requires Adobe Acrobat Reader)

  9. Kaufman, C. and Bingham, D. “Efficient Emulators of Computer Experiments Using Compactly Supported Correlation Functions,” UC Berkely Technical Report, 2009.

  10. Kennedy, J., and Eberhart, R., “Particle Swarm Optimization,” Proceedings, IEEE International Conference on Neural Networks, Vol. 4, 1995, pp. 1942-1948. (PDF , 626K, requires Adobe Acrobat Reader)

  11. Kennedy, M. C., and O'Hagan, A., “Predicting the output of a complex computer code when fast approximations are available,” Biometrika, Vol. 87, 2000, pp. 1-14. (PDF , 3000K, requires Adobe Acrobat Reader)

  12. Kennedy, M. C., and O'Hagan, A., “Bayesian calibration of computer models,” Biometrika, Vol. 63, 2001, pp. 425-454. (PDF , 228K, requires Adobe Acrobat Reader)

  13. Kleijnen, J. P. C. and van Beers, W. C. M., “Monotonicity-preserving Bootstrapped Kriging Metamodels,” TechnicalReport WP 6. Department of Information Systems and Management and Center for Economic Research,Tilburg University. Postbox 90153, 5000 LE Tilburg, Netherlands., 2009. (PDF , 228K, requires Adobe Acrobat Reader)

  14. Loeppky, Sacks, and Welch, “Choosing the sample size fo a computer experiment: A practical guide,” Technometrics, Vol. 51, 2009, pp. 366-376. (PDF , 330K, requires Adobe Acrobat Reader)

  15. McKay, M.D., Conover, R.J., and Beckman, R.J. “A comparison of three methods for selecting values of input variables in the analysis of output from a computer code,” Technometrics, Vol. 21, 1979, pp. 239-245. (PDF , 1130K, requires Adobe Acrobat Reader)

  16. Oakley, J. “Estimating percentiles of uncertain computer code outputs,” Appl. Statist., Vol. 53, No.1, 2004, pp. 83-93. (PDF , 124K, requires Adobe Acrobat Reader)

  17. Oakley, J., and O'Hagan, A., “Probabilistic sensitivity analysis of complex models: a Bayesian approach,” J. R. Statist. Soc. B, Vol. 66, No.3, 2004, pp. 751-769. (PDF , 344K, requires Adobe Acrobat Reader)

  18. Qian, Z., Wu, H. and Wu, C. F. J., “Gaussian process models for computer experiments with qualitative and quantitative factors,” Technometrics, Vol. 50, 2008, pp. 383-396. (PDF , 637K, requires Adobe Acrobat Reader)

  19. Sacks, J., Welch, W. J., Mitchell, T. J, and Wynn, H. P., “Design and analysis of computer experiments,” Statistical Science, Vol. 4, No.4, 1989, pp. 409-435. (PDF , 2700K, requires Adobe Acrobat Reader)

  20. Schonlau, M. and Welch, W. J., “Screening the input variables to a computer model via analysis of variance and visualization,” Screening Methods for Experimentation in Industry, Drug Discovery, and Genetics. Editors Dean, A. and Lewis, S., Springer 2006, pp. 308-327. (PDF , 653K, requires Adobe Acrobat Reader)

  21. Svenson, J. D. and Santner, T. J., “Multiobjective Optimization of Expensive Black-Box Functions via Expected Maximin Improvement,” To appear in Optimization and Engineering (PDF , 299K, requires Adobe Acrobat Reader)

  22. Tang, B. “Orthogonal array-based latin hypercubes,” JASA, Vol. 88, 1993, pp. 1392-1397. (PDF , 1100K, requires Adobe Acrobat Reader)

  23. Welch, W. “Branch-and-Bound Search for Experimental Designs Based on D Optimality and Other Criteria,” Technometrics, Vol. 24, 1982, pp. 41-48. (PDF , 229K, requires Adobe Acrobat Reader)

  24. Welch, W. “Computer-Aided of Design Experiments for Estimation Response,” Technometrics, Vol. 26, 1984, pp. 217-224. (PDF , 1160K, requires Adobe Acrobat Reader)



Technical Reports, etc.

  1. Bayarri, M. J., Berger, J. O., Paulo, R., Sacks, J., Cafeo, J. A., Cavendish, J., Lin, C. H., and Tu, J., “A framework for validation of computer models,” (PDF , 388K, requires Adobe Acrobat Reader)

  2. Joseph, V.R., “Limit Kriging,” School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA. (PDF , 238K, requires Adobe Acrobat Reader)

  3. Higdon, D., Gattiker, J., Williams, “Computer Model Calibration Using High-Dimensional Data,” Los Alamos National Laboratory. (PDF , 1099K, requires Adobe Acrobat Reader)

  4. Marin, O., “Sobol sequences ” (pdf , 315K, requires Adobe Acrobat Reader)

  5. Notz, W., “Some SAS code ” (PDF , 784K, requires Adobe Acrobat Reader)

  6. Zhou, Q., Qian P. Z .G., Paulo, Zhou, S., “A simple approach to emulation for computer models with qualitative and quantitative factors,” (PDF , 225K, requires Adobe Acrobat Reader)



Computer Experiments Journal Club



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E-Mail: win@stat.osu.edu
Last modified on: August 29, 2013