analysis.sensitivity: Runs a series of sensitivity analyses by a function from the...
In multisensi: Multivariate Sensitivity Analysis

Description Usage Arguments Details Value Examples

The analysis.sensitivity function runs a series of sensitivity analyses on the columns of a data.frame, using a method implemented in the sensitivity package.

1 2	analysis.sensitivity(Y, plan, nbcomp = 2, sigma.car = NULL, analysis.args = list(keep.outputs = FALSE))

`Y`	a data.frame of output variables or principal components.
`plan`	an object containing the design. It must be created by a function from the sensitivity package with argument `model=NULL`.
`nbcomp`	the number of `Y` variables to analyse (the first `nbcomp` variables of `Y` will be analysed).
`sigma.car`	NULL or sum of squares of Y. If not NULL, compute the Generalised Sensitivity Indices (saved in the last column of the data.frame mSI/tSI/iSI outputs.
`analysis.args`	a list of arguments. If it contains `keep.outputs=TRUE`, the outputs associated with the analysis of each variable are returned (see section `Value`).

The argument plan must be an object created by a method implemented in the sensitivity package. Thus it belongs to a class such as morris or fast99. The name of the class is stored in the element call.info$fct of the output returned by analysis.sensitivity.

A list containing:

`SI`	data.frame of sensitivity indices or other importance measures returned by the function from the sensitivity package used. Sometimes empty but kept for compatibility reasons.
`mSI`	data.frame of first-order sensitivity indices
`tSI`	data.frame of total sensitivity indices
`iSI`	data.frame of interaction sensitivity indices
`inertia`	empty (kept for compatibility reasons)
`indic.fact`	0-1 matrix to indicate the factors associated with each factorial effect
`Hpredict`	empty (kept for compatibility reasons)
`outputkept`	if `analysis.args$keep.outputs=TRUE`, list of the outputs returned by the sensitivity analysis performed on each variable
`call.info`	list with first element `analysis="sensitivity"` and second element `fct` storing the class name of the argument `plan`

# Test case : the Winter Wheat Dynamic Models (WWDM)
library(sensitivity) # to use fast99
# input factors design
data(biomasseX)
# input climate variable
data(Climat)

# example of the sensitivity:fast99 function
# design
newplan <- fast99(model = NULL, factors = names(biomasseX), n = 100, 
            q = "qunif", q.arg = list(list(min = 0.9, max = 2.8),
                         list(min = 0.9, max = 0.99),
                         list(min = 0.6, max = 0.8),
                         list(min = 3, max = 12),
                         list(min = 0.0035, max = 0.01),
                         list(min = 0.0011, max = 0.0025),
                         list(min = 700, max = 1100)))
# simulations
wwdm.Y <- simulmodel(model=biomasse, plan=newplan$X, climdata=Climat)
# analysis
res <- analysis.sensitivity(data.frame(wwdm.Y), plan=newplan, nbcomp=4)