multisensi (version 2.1-1)

dynsi: Dynamic Sensitivity Indices: DSI

Description

dynsi implements the Dynamic Sensitivity Indices. This method allows to compute classical Sensitivity Indices on each output variable of a dynamic or multivariate model by using the ANOVA decomposition

Usage

dynsi(formula, model, factors, cumul = FALSE, simulonly=FALSE,
      nb.outp = NULL, Name.File=NULL, ...)

Arguments

formula

ANOVA formula like "A+B+c+A:B" OR an integer equal to the maximum interaction order in the sensitivity model.

model

output data.frame OR the name of the R-function which calculates the model output. The only argument of this function must be a vector containing the input factors values.

factors

input data.frame (the design) if model is a data.frame OR a list of factors levels such as factor.example <- list(A=c(0,1),B=c(0,1,4)).

cumul

logical value. If TRUE the sensitivity analysis will be done on the cumalative outputs.

simulonly

logical value. If TRUE the program stops after calculating the design and the model outputs.

nb.outp

The first nb.outp number of model outputs to be considered. If NULL all the outputs are considered.

Name.File

optional name of a R script file containing the R-function that calculates the simulation model. e.g "exc.ssc".

...

possible fixed parameters of the model function.

Value

dynsi returns a list of class "dynsi" containing the following components:

X

a data.frame containing the experimental design (input samples)

Y

a data.frame containing the output (response)

SI

a data.frame containing the Sensitivity Indices (SI) on each output variable of the model and the Generalised SI (GSI)

mSI

a data.frame of first order SI on each output variable and first order GSI

tSI

a data.frame containing the total SI on each output variable and the total GSI

iSI

a data.frame of interaction SI on each output variable and interaction GSI

Att

0-1 matrix of association between input factors and factorial terms in the anovas

call.info

a list containing informations on the process (reduction=NULL, analysis, fct, call)

inputdesign

either the input data.frame or the sensitivity object used

outputs

a list of results on each output variable

...

Details

If factors is a list of factors, the dynsi function generates a complete factorial design. If it is a data.frame, dynsi expects that each column is associated with an input factor.

References

M. Lamboni, D. Makowski and H. Monod, 2009. Multivariate global sensitivity analysis for dynamic crop models. Field Crops Research, 113, 312-320.

A. Saltelli, K. Chan and E. M. Scott eds, 2000. Sensitivity Analysis. Wiley, New York.

See Also

gsi, multisensi

Examples

# NOT RUN {
# Test case : the Winter Wheat Dynamic Models (WWDM)
# input factors design,
 data(biomasseX)
# input Climate variables
 data(Climat)
# output variables (precalculated to speed up the example)
 data(biomasseY)
#
 DYNSI <- dynsi(2, biomasseY, biomasseX)
 summary(DYNSI)
 print(DYNSI)
 plot(DYNSI, color=heat.colors)
 #graph.bar(DYNSI,col=1, beside=F)  # sensitivity bar plot
                                    # for the first output (col=1)
 #graph.bar(DYNSI,col=2, xmax=1)    #
  
# }