Xifu Sun

TL;DR: A multidisciplinary group of researchers and practitioners revisit the current status of Sensitivity analysis, and outline research challenges in regard to both theoretical frameworks and their applications to solve real-world problems.

TL;DR: In this article, sensitivity analysis (SA) has been used to assess model sensitivities to input parameter values in a water quality model, including plant stress threshold (f), coefficient of evapotranspiration (e), catchment moisture threshold (d), in decreasing order, indicating that sediment and nutrient loads are more sensitive to parameters that affect the magnitude of flows than those (v"s, @t^q,@t^s) that control the timing and shape of the peak in a time series.

TL;DR: A step-by-step pragmatic framework to guide Sensitivity analysis, with an emphasis on addressing potential uncertainty sources related to spatial datasets and the consequent impact on model predictive uncertainty in SD-EMs is proposed.

TL;DR: In this article, the Column Shift method is applied to variance-based sensitivity analysis of the V-function, with much higher accuracy than commonly used randomization methods in most circumstances.

TL;DR: In this paper , the authors compare activity scoring with the Sobol' and the Morris global methods using a series of well-known benchmark test functions with exactly computable sensitivities, and analyse the accuracy, efficiency, impact of sampling method, convergence rate, and confidence interval estimation through both bootstrapping and replication.