Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

ABSTRACT: Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling

SUBMITTER: Xu C 

PROVIDER: S-EPMC3798038 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature