Metamodels and the Bootstrap for Input Model Uncertainty Analysis
Seminar Room 1, Newton Institute
The distribution of simulation output statistics includes variation form the finiteness of samples used to construct input probability models. Metamodels and bootstrapping provide a way to characterize this error. The metamodel-fiting experiment benefits from a sequential design strategy. We describe the elements of such a strategy, and show how they impact performance.