摘要

Global sensitivity analysis is widely used in many areas of science, biology, sociology and policy planning. The variance-based methods also known as Sobol' sensitivity indices has become the method of choice among practitioners due to its efficiency and ease of interpretation. For complex practical problems, estimation of Sobol' sensitivity indices generally requires a large number of function evaluations to achieve reasonable convergence. To improve the efficiency of the Monte Carlo estimates for the Sobol' total sensitivity indices we apply the control variate reduction technique and develop a new formula for evaluation of total sensitivity indices. Presented results using well known test functions show the efficiency of the developed technique.

  • 出版日期2015-2