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delsa
implements Distributed Evaluation of
Local Sensitivity Analysis to calculate first order parameter
sensitivity at multiple locations in parameter space. The locations
in parameter space can either be obtained by a call to parameterSets
or by specifying X0
directly, in which case the prior variance
of each parameter varprior
also needs to be specified. Via plot
(which uses functions of the package ggplot2
and reshape2
),
the indices can be visualized.delsa(model = NULL, perturb=1.01,
par.ranges, samples, method,
X0, varprior,
...)
## S3 method for class 'delsa':
tell(x, y = NULL,\dots)
## S3 method for class 'delsa':
print(x, \dots)
## S3 method for class 'delsa':
plot(x, which=1:3, ask = dev.interactive(), ...)
predict
method,
defining the model to analyze."grid"
and
"innergrid"
method, corresponds to the number of samples for
each parameter, and may be a vector.parameterSets
method
X0
is specified, varprior
must also be specified.model
which are passed
unchanged each time it is called."delsa"
storing the state of the
sensitivity study (parameters, data, estimates).par(ask=.)
delsa
returns a list of class "delsa"
, containing all
the input arguments detailed before, plus the following components:data.frame
containing the design of experiments.X0
print
shows summary of the first order indices across parameter space.
plot
shows: (1) the cumulative distribution function of first order
sensitivity across parameter space, (2) variation of first order sensitivity
in relation to model response, and (3) sensitivity in relation to parameter value.parameterSets
which is used to generate points, sensitivity
for other methods in the package# Test case : the non-monotonic Sobol g-function
# (there are 8 factors, all following the uniform distribution on [0,1])
library(randtoolbox)
x <- delsa(model=sobol.fun,
par.ranges=replicate(8,c(0,1),simplify=FALSE),
samples=100,method="sobol")
# Summary of sensitivity indices of each parameter across parameter space
print(x)
library(ggplot2)
library(reshape2)
x11()
plot(x)
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