An effective algorithm for computing global sensitivity indices (EASI)

We present an algorithm named EASI that estimates first order sensitivity indices from given data using Fast Fourier Transformations. Hence it can be used as a post-processing module for pre-computed model evaluations. Ideas for the estimation of higher order sensitivity indices are also discussed.