mtk (version 1.0)

Regression: The Regression Method

Description

A mtk compliant implementation of the src method for computing the sensitivity index based on standardized (rank) regression coefficients.

Usage

• mtkRegressionAnalyser(listParameters = NULL)
• mtkNativeAnalyser(analyze="Regression", information=NULL)

Parameters used to manage the method

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.

Details

1. The mtk implementation uses the src function of the package sensitivity. For further details on the arguments and the behavior, see help(src, sensitivity).
2. 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.

References

A. Saltelli, K. Chan and E. M. Scott (2000). Sensitivity Analysis, Edition Wiley

See Also

help(src, sensitivity)

Examples

# 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)