Derivative based Global Sensitivity Measure Method
struct DGSM <: GSAMethod
    crossed::Bool 
endThe 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)