A Bayesian Monte Carlo-based method for efficient computation of global sensitivity indices

Global sensitivity analysis, such as Sobol’ indices, plays an important role for quantifying the relative importance of random inputs to the response of complex model, and the estimation of Sobol’ indices is a challenging problem. In this paper, Bayesian Monte Carlo method is employed for developing a new technique to estimate the Sobol' indices with low computational cost. In the developing technique, the output response is expanded as the sum...