example_model2: Functions to demonstrate FAST
In fast: Implementation of the Fourier Amplitude Sensitivity Test (FAST)

Description Usage Arguments Value Author(s) References See Also Examples

Model 1 depends on a flexible number of parameters. It is documented in Saltelli and Sobol 1995 and Davis and Rabinowith 1984.

Model 2 depends on 4 parameters. It produces a weighted sum of the 4 parameters and returns this sum. The weights depend on an additional parameter x=1:200.

1 2	example_model1(par,a, output=c("model", "analytical sensitivities")) example_model2(p, fig=FALSE)

`par`	A vector with parameters
`a`	A vector with a values of the same length as par. `a` is a measure for the importance of each parameter, with highest importance for a=0, non important parameters for a=9 and neglegible parameters for a=99
`output`	A character indicating whether to return the model results or the analytical parameter sensitivities
`p`	A vector of 4 parameters
`fig`	boolean: Plot the model(x)

A vector of the weighted sum of parameters.

Dominik Reusser

Saltelli, Andrea, and Ilya M Sobol. "About the use of rank transformation in sensitivity analysis of model output." Reliability Engineering & System Safety 50, no. 3 (1995): 225-239.

Davis, P. J. & Rabinowitz, P., Methods of Numerical Integration, 2nd edition, Academic Press, New York, 1984.

fast, sensitivity_rep

example_model1(par=c(0.5,0.5,0.5),a=c(1,1,1))

#The model depends on 4 parameters
#
#It produces a weighted sum of the 4 parameters and returns this sum
#
#The weights depend on an additional parameter x=1:200 
example_model2(p=c(1,3,1,1),fig=TRUE)
example_model2(p=c(1,2,2,3),fig=TRUE)