Global Sensitivity Analysis

gsa(f, method::GSAMethod, param_range; samples, batch=false)

where:

• y=f(x) is a function that takes in a single vector and spits out a single vector or scalar. If batch=true, then f takes in a matrix where each row is a set of parameters, and returns a matrix where each row is a the output for the corresponding row of parameters.
• method is one of the available GSA methods.
• param_range is a vector of tuples for the upper and lower bound for the given parameter i.
• samples is a required keyword argument for the number of samples of parameters for the design matrix. Note that this is not relevant for Fractional Factorial Method and Morris Method.

Additionally,

For Delta Moment-Independent Method, EASI Method and Regression Method input and output matrix based method as follows is available:

res = gsa(X, Y, method)

where:

• X is the number of parameters * samples matrix with parameter values.
• Y is the output dimension * number of samples matrix with out evaluated at X's columns.
• method is one of the GSA methods below.

For Sobol Method one can use the following design matrices based method instead of parameter range based method discussed earlier:

effects = gsa(f, method, A, B; batch=false)

where A and B are design matrices with each row being a set of parameters. Note that generate_design_matrices from QuasiMonteCarlo.jl can be used to generate the design matrices.