Uncertainty Quantification of the Ishigami Function

Application ID: 103131

This example demonstrates how to perform uncertainty quantification analysis of the Ishigami function. This random function of three variables is a well-known benchmark used to test global sensitivity analysis and uncertainty quantification algorithms. The mean, standard deviation, maximum, and mininum values as well as Sobol indices of the Ishigami function can be calculated analytically for the input distributions used here. A separate version of this model is provided which performs a direct Monte Carlo simulation using no add-on products.

This model example illustrates applications of this type that would nominally be built using the following products: