Sensitivity Analysis in Practice

Music City Center 

The modern practitioner of uncertainty quantification (UQ) for complex models is fortunate to have at their disposal developments from more than three decades of research in the field of computer experiments. Major developments include efficient design schemes, elegant approaches to combining data sources, and innovative techniques for sensitivity analysis. Sensitivity analysis seeks to explain uncertainty in model outputs based on uncertainty in model inputs. In this talk, we describe various sensitivity analysis approaches with an eye toward their practical use. We describe approaches that utilize many model runs like Sobol, Shapley, and delta sensitivity, as well as approaches that require fewer model runs like derivative-based global sensitivity measures and design-based approaches. We also discuss the practical utility of emulators for sensitivity analysis and a few open questions.

Sobol sensitivity

emulator

computer experiment

uncertainty quantification