Sobol Sensitivity indices
These examples serve as a guide for using the Sobol sensitivity module. They have been taken from various papers to enable validation of the implementation and have been referenced accordingly.
Single output models
We demonstrate the computation of the Sobol indices for models with a single output using the following examples:
Additive function
This is a beginner-friendly example for introducing Sobol indices. The function is a linear combination of two inputs which produces a scalar output.
Ishigami function
The Ishigami function is a non-linear, non-monotonic function that is commonly used to benchmark uncertainty and senstivity analysis methods.
Sobol function
The Sobol function is non-linear function that is commonly used to benchmark uncertainty and senstivity analysis methods. Unlike the Ishigami function which has 3 input variables, the Sobol function can have any number of input variables (see [2]).
Multiple output models
We demonstrate the computation of the Sobol indices for models with multiple outputs using the following example:
Mechanical oscillator ODE
