# Derivative based Global Sensitivity Measure Method

struct DGSM <: GSAMethod
crossed::Bool
end

The keyword arguments for DGSM are as follows:

• crossed: A string(True/False) which act as indicator for computation of DGSM crossed indices. Defaults to false.

## Method Details

The DGSM method takes a probability distribution for each of the parameters and samples are obtained from the distributions to create random parameter sets. Derivatives of the function being analysed are then computed at the sampled parameters and specific statistics of those derivatives are used. The paper by Sobol and Kucherenko discusses the relationship between the DGSM results, tao and sigma and the Morris elementary effects and Sobol Indices.

### API

function gsa(f, method::DGSM, dist::AbstractArray; samples::Int, kwargs...)

dist: Array of distribution of respective variables. E.g. dist = [Normal(5,6),Uniform(2,3)] for two variables.

### Example

using GlobalSensitivity, Test, Distributions

samples = 2000000

f1(x) = x[1] + 2*x[2] + 6.00*x[3]
dist1 = [Uniform(4,10),Normal(4,23),Beta(2,3)]
b =  gsa(f1,DGSM(),dist1,samples=samples)