An efficient method for estimating various variance-based sensitivity indices

In order to simultaneously estimate various variance-based sensitivity indices, a method is proposed by combining space-partition idea and unscented transformation (UT) method, which can estimate variance-based global sensitivity index (Sobol index), variance-based regional sensitivity index and variance-based W index by repeatedly using a set of UT samples. Besides, a modified variance-based W index is proposed, which can analyze the sensitivity of the model input variables comprehensively and reasonably. What'smore, the modified variance-based W index includes both the original one and the variability of effect on the variance of model output when the model input variable is fixed in different intervals. Thus, the modified one more reasonably reflects the average impact on the variance of the model output when model input variable is fixed in different intervals. The results of numerical and engineering examples illustrate the accuracy and efficiency of the proposed method and the reasonability of the modified variance-based W index.