Sensitivity analysis of graphical functions

Despite high degrees of uncertainty associated with graphical functions, sensitivity analysis of these functions has received less attention than parametric sensitivity analysis. Recently, a promising method was proposed in the literature to generate alternative functional forms, reducing the problem to that of parametric sensitivity. Yet the usability of the method for graphical functions in system dynamics has not been investigated. We apply this function distortion method to a sample model and identify a number of shortcomings, such as a limited variety of alternative forms. We then propose extensions to the method to address the shortcomings, and subsequently test the extensions. We find the (extended) method of function distortion to be readily applicable and efficient in testing the sensitivity of model outputs to variations in the form of graphical functions. The proposed extensions increase the variety of possible distortions, but further research can be conducted on the control of the distortions.