Shourtcourse on computer model calibration

Statistical Methodology and Tools for:

• The Analysis of Computer Experiments
• Combining Experimental Data with Computer Simulation Models for Calibration and Prediction

Notes

• stat methodology slides Slides covering basic methodolgies relevant to the GPM/SA code
• gpmsa tutorial slides Slides/notes on how to set up and run the GPM/SA code
• GPMSAmanual.pdf a crude manual for the GMP/SA code written by Jim Gattiker

Semi-Relevant Manuscripts

■ LAUR-05-6410 D. Higdon, J. Gattiker and B. Williams (2005). Computer Model Calibration using High Dimensional Output.

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LAUR-04-1745 D. Higdon, J. Gattiker and B. Williams (2005). Slides to go with: Computer Model Calibration using High Dimensional Output.

• LAUR-05-4951 B. Williams, D. Higdon, J. Gattiker, L. Moore, M. D. McKay and S. Keller-McNulty (2006). Combining Experimental Data and Computer Simulations, with an Application to Flyer Plate Experiments.
• LAUR-03-8524 C. Linkletter, D. Bingham, N. Hengartner, D. Higdon, K. Ye (2006). Variable Selection for Gaussian Process Models in Computer Experiments
• manuscript M. A. Christie, J. Glimm, J. W. Grove, D. Higdon, D. H. Sharp, M. M. Wood-Schultz (2005). Error Analysis and Simulation of Complex Phenomena, in Los Alamos Science
• LAUR-05-3097 D. Higdon (2005). A Primer on Space-time Modeling from a Bayesian Perspective
• LAUR-03-2743 D. Higdon, M. Kennedy, J. Cavendish, John Cafeo and R. D. Ryne (2003). Combining Field Data and Computer Simulations for Calibration and Prediction
• manuscript D. Higdon, H. Lee and C. Holloman (2003). Markov Chain Monte Carlo-based approaches for inference in Computationally Intensive Inverse Problems.