List of Papers

Spring 2013 Talks

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

  2. Santner, T., “Sensitivity analysis, overview,” (PDF , 472K, requires Adobe Acrobat Reader)



Spring 2013 Papers

  1. Andianakis and Challenor, “The effect of the nugget on GP emulators,” Comp. Stat. and Data Analysis, Vol. 56, 2012, pp. 4215-4228. (PDF , 925K, requires Adobe Acrobat Reader)

  2. Ba and Joseph, “Composite Gaussian Process models,” Ann App Stat, Vol. 6, 2012, pp. 1838-1860. (PDF , 281K, requires Adobe Acrobat Reader)

  3. Bastos and O'Hagan, “Diagnostics for GP models,” Technometrics, Vol. 51, 2009, pp. 425-438. (PDF , 513K, requires Adobe Acrobat Reader)

  4. Bayarri et al., “Using statistical and computer models to quantify volcanic hazards,” Technometrics, Vol. 51, 2009, pp. 402-413. (PDF , 489K, requires Adobe Acrobat Reader)

  5. Campolongo, Cariboni, and Saltelli, “An effective screening design for sensitivity analysis of large models,” Environmental Modeling and Software, Vol. 22, 2007, pp. 1509-1518. (PDF , 235K, requires Adobe Acrobat Reader)

  6. Cioppa and Lucas, “Effiicient nearly orthogonal and space-filling latin hypercubes,” Technometrics, Vol. 49, 2007, pp. 45-55. (PDF , 271K, requires Adobe Acrobat Reader)

  7. Da Veiga, Wahl, and Gamboa, “Local polynomial estimation for sensitivity analysis on models with correlated inputs,” Technometrics, Vol. 51, 2009, pp. 452-463. (PDF , 371K, requires Adobe Acrobat Reader)

  8. Han et al., “Prediction for computer experiments having qualitative and quantitative input variables,” Technometrics, Vol. 51, 2009, pp. 278-288. (PDF , 296K, requires Adobe Acrobat Reader)

  9. Hung, Joseph, and Melkote, “Design and analysis of computer experiments with branching and nested factors” Technometrics, Vol. 51, 2009, pp. 354-365. (PDF , 768K, requires Adobe Acrobat Reader)

  10. Kennedy and Eberhart, “Partricle swarm optimization,” IEEE, 1995, pp. 1942-1948. (PDF , 626K, requires Adobe Acrobat Reader)

  11. 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)

  12. Rougier et al., “Expert knowledge and multivariate emulation: the thermosphere-ionosphere electrodynamics general circulation model (TIE-GCM)” Technometrics, Vol. 51, 2009, pp. 414-424. (PDF , 604K, requires Adobe Acrobat Reader)

  13. Saltelli and Becker, “Design for sensitivity analysis,” (PDF , 741K, requires Adobe Acrobat Reader)

  14. Taddy et al., “Bayesian guided pattern search for robust local optimization,” Technometrics, Vol. 51, 2009, pp. 389-401. (PDF , 1040K, requires Adobe Acrobat Reader)

  15. Viera Jr. et al., “Generating and improving orthogonal designs by using mixed integer programming,” European Journal of Operational Research, Vol. 215, 2011, pp. 629-638. (PDF , 183K, requires Adobe Acrobat Reader)

  16. Wang, Chen, and Tsui, “Bayesian validation of computer models,” Technometrics, Vol. 51, 2009, pp. 439-451. (PDF , 320K, requires Adobe Acrobat Reader)



746 Notes

  1. Lecture 1 (Fanfang) “General Analyisis of Block Designs,” (PDF , 1660K, requires Adobe Acrobat Reader)

  2. Lecture 2 (Fanfang) “Efficiency of designs,” (PDF , 1460K, requires Adobe Acrobat Reader)
    and “A note on efficiency factors (supplemental material from the web),” (PDF , 194K, requires Adobe Acrobat Reader)

  3. Lecture 3 (Svenson) “Latin Squares and Row-Column Designs (includes carry-over designs),” (PDF , 766K, requires Adobe Acrobat Reader)

  4. Lecture 4 (Dean) “Split Plot Designs Designs,” (PDF , 342K, requires Adobe Acrobat Reader)

  5. Lecture 5 (Fanfang) “Factorial designs,” (PDF , 1060K, requires Adobe Acrobat Reader)

  6. Lecture 6 (Fanfang) “Fractional factorial designs,” (PDF , 1040K, requires Adobe Acrobat Reader)

  7. Lectures 8 and 9 (Fanfang) “Orthogonal arrays and Taguchi,” (PDF , 2410K, requires Adobe Acrobat Reader)


Journal 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. 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)

  3. 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)

  4. 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)

  5. 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)

  6. 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)

  7. Huang,D.,Allen, T.T.,Notz,W.,Miller, R.A., “Sequential Kriging Optimization Using Multiple Fidelity Evaluations,” to appear in Structural and Multidisciplinary Optimization.

  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, 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)

  11. 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)

  12. 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)

  13. 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)

  14. 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)

  15. 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)

  16. 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)

  17. 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)

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

  19. 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)

  20. 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

  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. Hankin, R., “BACCO version 1.0-24 ” (file , 278K, zipped file)

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

  6. Notz, W., “Bacco emulator example ” (file , 12K, text file)

  7. Notz, W., “Bacco calibrator example ” (file , 72K, text file)

  8. Notz, W., “Emulator example ” (file , 4K, text file)

  9. Notz, W., “Some R code for the gaussian correlation function ” (file , 4K, text file)

  10. Notz, W., “Some R code for the cubic correlation function ” (file , 4K, text file)

  11. Notz, W., “Some R code for the multidimensional cubic correlation function ” (file , 4K, text file)

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

  13. Notz, W., “Some notes on design ” (pdf , 536K, requires Adobe Acrobat Reader)

  14. Notz, W., “JSM 2006 IOL design talk ” (pdf , 332K, requires Adobe Acrobat Reader)

  15. 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)

BACCO Software

  1. Calibrator.zip
  2. Approximator.zip
  3. Emulator.zip


Computer Experiments Journal Club



© Copyright 2012 Computer Experiments OSU Department of Statistics
E-Mail: win@stat.ohio-state.edu
Last modified on: Jan. 13, 2012