Sensitivity Analysis Methods

Abstract

Sensitivity analysis (SA) is an important tool for assessing and reducing uncer- tainties in computer-based models. This chapter presents a comprehensive review of some commonly used SA methods, including gradient-based, variance-based, and regression-based methods. Features and applicability of those methods are described and illustrated with some examples. Merits and limitations of different methods are explained, and the criteria of choosing appropriate SA methods for different applications are suggested.