ABSTRACT
We show that variance-based, density-based, expected-value of information based sensitivity measures rest on the same rationale, namely, information updating. We prove general results concerning their properties. We then show that they can all be estimated by the same design. The design is suitable in the presence of correlated inputs and makes the estimation cost independent of the number of model inputs and depending solely on the sample size. Results of numerical experiments are proposed.
