mtk (version 1.0)

mtkMorrisAnalyser-class: The mtkMorrisAnalyser class

Description

The mtkMorrisAnalyser class is a sub-class of the class mtkAnalyser. It implements the sensitivity analysis method Morris and provides all the slots and methods defined in the class mtkAnalyser.

Class Hierarchy

Parent classes :

mtkAnalyser

Direct Known Subclasses :

Constructor

mtkMorrisAnalyser

signature(mtkParameters = NULL, listParameters = NULL)

Slots

name:

(character) always takes the string "analyze".

protocol:

(character) always takes the string "R".

site:

(character) always takes the string "mtk".

service:

(character) always takes the string "Morris".

parameters:

(vector) a vector of [mtkParameter] containing the parameters to pass while calling the service.

ready:

(logical) a logical to tell if the process is ready to run.

state:

(logical) a logical to tell if the results produced by the process are available and ready to be consumed.

result:

(ANY) a data holder to hold the results produced by the process

Methods

setName

signature(this = "mtkMorrisAnalyser", name = "character"): Not used, method inherited from the parent class.

setParameters

signature(this = "mtkMorrisAnalyser", f = "vector"): Assigns new parameters to the process.

getParameters

signature(this = "mtkMorrisAnalyser"): Returns the parameters as a named list.

is.ready

signature( = "mtkMorrisAnalyser"): Tests if the process is ready to run.

setReady

signature(this = "mtkMorrisAnalyser", switch = "logical"): Makes the process ready to run.

is.ready

signature( = "mtkMorrisAnalyser"): Tests if the results produced by the process are available.

setReady

signature(this = "mtkMorrisAnalyser", switch = "logical"): Marks the process as already executed.

getResult

signature(this = "mtkMorrisAnalyser"): Returns the results produced by the process as a [mtkMorrisAnalyserResult].

getData

signature(this = "mtkMorrisAnalyser"): Returns the results produced by the process as a data.frame.

serializeOn

signature(this = "mtkMorrisAnalyser"): Returns all data managed by the process as a named list.

run

signature(this = "mtkMorrisAnalyser", context= "mtkExpWorkflow"): Runs the process to generate the results.

summary

signature(object = "mtkMorrisAnalyser"): Provides a summary of the results produced by the process.

print

signature(x = "mtkMorrisAnalyser"): Prints a report of the results produced by the process.

plot

signature(x = "mtkMorrisAnalyser"): Plots the results produced by the process.

report

signature(this = "mtkMorrisAnalyser"): Reports the results produced by the process.

References

1. Campolongo, F., J. Cariboni, and A. Saltelli (2007). An effective screening design for sensitivity analysis of large models. Environmental Modelling and Software, 22, 1509–1518.
2. A. Saltelli, K. Chan and E. M. Scott (2000). Sensitivity Analysis. Wiley, New York

See Also

help(morris, sensitivity) and help(Morris)

Examples

## Sensitivity analysis of the "Ishigami" model with the "Morris" method 


#	Generate the factors
		data(Ishigami.factors)
		
# 	Build the processes and workflow:

#   1) the design process
		exp1.designer <- mtkMorrisDesigner( listParameters
	    	= list(r=20, type="oat", levels=4, grid.jump=2)) 

#   2) the simulation process
		exp1.evaluator <- mtkNativeEvaluator(model="Ishigami") 

#   3) the analysis process 
		exp1.analyser <- mtkMorrisAnalyser()

#   4) the workflow

		exp1 <- mtkExpWorkflow(expFactors=Ishigami.factors,
	    processesVector = c(design=exp1.designer,
		evaluate=exp1.evaluator, analyze=exp1.analyser))

# 	Run the workflow and report the results.
		run(exp1)
		print(exp1)