Sensitivity Analysis

Sensitivity analysis (SA) studies how much the uncertainty of a model output depends upon its inputs. Though it is generally agreed in existing guidelines that uncertainty and sensitivity analyses are both crucial for the validation or verification of a model, their application is hampered by practical difficulties, scarce awareness, and at times reluctance to expose the weakness of a model. We present here global sensitivity analysis, mainly through one class of global SA methods known as ‘variance-based’ – considered by most practitioners as a recommended practice - and offer pointers on additional methods. We also suggest several hints for a successful and effective use these of these techniques