fast is the implementation of the Fourier Amplitude Sensitivity
Test. This function computes the following non-linear indices of
sensitivity: first-order indices and total indices.fast(model = NULL, factors, n, M = 4,
G = "uniform", min = 0, max = 1, omega = NULL, ...)
## S3 method for class 'fast':
compute(sa, y = NULL)model which are passed
unchanged each time it is called.fast returns an object of class "fast".
An object of class "fast" is a list containing the following
components:model is a function or a predictor (a class with a
predict method) computing the response y based on the
sample given by x. If no model is specified, the indices will be
computed when one gives the response. The space transformation G is the function such that:
$$x_i = G_i(\mathrm{sin}(\omega_i s))$$
It must be a function of two parameters (G <- function(i, x)
...). If the string "uniform" is given, then the function is
the best one for uniform factors on the range $[a_i, b_i]$:
$$G_i(x) = a_i + (b_i-a_i) \times \left( \frac{1}{2} + \frac{1}{\pi}
\mathrm{asin}(x) \right)$$
where $a_i$ and $b_i$ are the boundaries given by
the arguments min and max. min and max can
be single values (the same for each factor) or vectors.
If the set of frequencies omega is not given, the function use
the set recommended by Saltelli (the so-called extended-FAST). The
first frequency is the greater, corresponding to the index of
interest, and the other correspond to the complementary set.
Saltelli, A., Chan, K. and Scott, E. M., 2000, Sensitivity analysis. Wiley.
Cukier, R. I., Levine, H. B. and Schuler, K. E., 1978, Nonlinear sensitivity analysis of multiparameter model systems. J. Comput. Phys., 26, 1--42.
sensitivity
compute# Test case : the non-monotonic Sobol g-function
sa <- fast(model = sobol.fun, factors = 8, n = 1000)
print(sa)
plot(sa)Run the code above in your browser using DataLab