Papers co-authored by Michael D. McKay and related to

Statistical Methods for Understanding and Quantifying Uncertainty in Predictions from Computer Models


Here is an overview of the way I look at the statistical analysis problem.

Material in slides from the presentations "Introduction to Statistical Methods for Understanding Prediction Uncertainty in Simulation Models" and "Sensitivity Analysis When Model Outputs Are Functions" is drawn from the papers in the section, below, on methodology.

Overviews of methodology

Examining variance-based (R2) sensitivity measures

Selecting input values for computer experiments

Combining experimental data and computer simulations

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Last modified 12 December 2010