Description Class Hierarchy Constructor Slots Methods References See Also Examples
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
.
mtkAnalyser
mtkMorrisAnalyser
signature(mtkParameters = NULL, listParameters = NULL)
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
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.
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.
A. Saltelli, K. Chan and E. M. Scott (2000). Sensitivity Analysis. Wiley, New York
help(morris, sensitivity)
and help(Morris)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ## 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)
|
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