sensitivity (version 1.18.1)

decoupling: Decoupling Simulations and Estimations

Description

tell and ask are S3 generic methods for decoupling simulations and sensitivity measures estimations. In general, they are not used by the end-user for a simple R model, but rather for an external computational code. Most of the sensitivity analyses objects of this package overload tell, whereas ask is overloaded for iterative methods only.

Usage

tell(x, y = NULL, …)
ask(x, …)

Arguments

x

a typed list storing the state of the sensitivity study (parameters, data, estimates), as returned by sensitivity analyses objects constructors, such as src, morris, etc.

y

a vector of model responses.

…

additional arguments, depending on the method used.

Value

tell doesn't return anything. It computes the sensitivity measures, and stores them in the list x. Side effect: tell modifies its argument x.

ask returns the set of data to simulate.

Details

When a sensitivity analysis method is called with no model (i.e. argument model = NULL), it generates an incomplete object x that stores the design of experiments (field X), allowing the user to launch "by hand" the corresponding simulations. The method tell allows to pass these simulation results to the incomplete object x, thereafter estimating the sensitivity measures.

When the method is iterative, the data to simulate are not stored in the sensitivity analysis object x, but generated at each iteration with the ask method; see for example sb.

Examples

# NOT RUN {
# Example of use of fast99 with "model = NULL"
x <- fast99(model = NULL, factors = 3, n = 1000,
            q = "qunif", q.arg = list(min = -pi, max = pi))
y <- ishigami.fun(x$X)
tell(x, y)
print(x)
plot(x)
# }