Statistical Modeling and Uncertainty Quantification of Computer Simulations, Fall 2020
Description: This special topic course is designed for our Ph.D. students. The course aims at equipping Ph.D. students, typically third-year and beyond, with a solid foundation on the concepts, methods, and tools in statistical modeling and uncertainty quantification of computer simulations.
Topics:
– Introductions to computer experiments
– Space-filling design
– Gaussian process modeling
– Prediction and Uncertainty Quantification
– Calibration
Textbook: Santner, T. J., Williams, B. J., and Notz, W. I. (2003). The Design and Analysis of Computer
Experiments. Springer.
References: Michael L. Stein (1999). Interpolation of Spatial Data: Some Theory for Kriging. Springer.