Description Usage Parameters used to manage the method Details References See Also Examples
A mtk
compliant implementation of the src
method for computing the sensitivity index based on standardized (rank) regression coefficients.
mtkRegressionAnalyser(listParameters = NULL)
mtkNativeAnalyser(analyze="Regression", information=NULL)
rank
:logical. If TRUE, the analysis is done on the ranks (default is FALSE
). See the help on function src
in the package sensitivity
.
nboot
:the number of bootstrap replicates (default 100). See the help on function src
in the package sensitivity
.
conf
:the confidence level for bootstrap confidence intervals (default 0.95). See the help on function src
in the package sensitivity
.
The mtk
implementation uses the src
function of the package sensitivity
. For further details on the arguments and the behavior, see help(src, sensitivity)
.
The implementation of the "Regression" method includes the class mtkRegressionAnalyser
to manage the analysis task and the
class mtkRegressionAnalyserResult
to manage the results produced by the analysis process.
A. Saltelli, K. Chan and E. M. Scott (2000). Sensitivity Analysis, Edition Wiley
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | # Uses the method "Regression" to analyze the model "Ishigami":
# Generate the factors
data(Ishigami.factors)
# Builds experiment design with the Monte-Carlo method
designer <- mtkBasicMonteCarloDesigner( listParameters=list(size=20) )
# Builds a simulator for the model "Ishigami" with the defined factors
model <- mtkNativeEvaluator("Ishigami" )
# Builds an analyser with the method "Regression" implemented in the package "mtk"
analyser <- mtkNativeAnalyser("Regression", information=list(nboot=20) )
# Builds a workflow to manage the processes scheduling.
ishiReg <- mtkExpWorkflow( expFactors=Ishigami.factors,
processesVector=c(design=designer, evaluate=model, analyze=analyser) )
# Runs the workflow et reports the results
run(ishiReg)
summary(ishiReg)
plot(ishiReg)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.