delsa: Distributed Evaluation of Local Sensitivity Analysis

In sensitivity: Global Sensitivity Analysis of Model Outputs and Importance Measures

Distributed Evaluation of Local Sensitivity Analysis

Description

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.

Usage

delsa(model = NULL, perturb=1.01,
  par.ranges, samples, method,
  X0, varprior, varoutput,
  ...)
  
## S3 method for class 'delsa'
tell(x, y = NULL,...)

## S3 method for class 'delsa'
print(x, ...)

## S3 method for class 'delsa'
plot(x, which=1:3, ask = dev.interactive(), ...)

Arguments

model	a function, or a model with a predict method, defining the model to analyze.
perturb	Perturbation used to calculate sensitivity at each evaluation location
par.ranges	A named list of minimum and maximum parameter values
samples	Number of samples to generate. For the "grid" and "innergrid" method, corresponds to the number of samples for each parameter, and may be a vector.
method	Sampling scheme. See parameterSets
X0	Parameter values at which to evaluate sensitivity indices. Can be used instead of specifying sampling method
varprior	Prior variance. If X0 is specified, varprior must also be specified.
varoutput	Output variance. If "summation" is specified (default value), the ouput variance is computed by summing the first order effects. If "empirical" is specified, the ouput variance is estimated frome the output sample.
...	any other arguments for model which are passed unchanged each time it is called.
x	a list of class "delsa" storing the state of the sensitivity study (parameters, data, estimates).
y	a vector of model responses.
which	if a subset of the plots is required, specify a subset of the numbers 1:3
ask	logical; if TRUE, the user is asked before each plot, see par(ask=.)

Details

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.

Value

delsa returns a list of class "delsa", containing all the input arguments detailed before, plus the following components:

call	the matched call.
X	a data.frame containing the design of experiments.
y	a vector of model responses.
delsafirst	the first order indices for each location in X0.
deriv	the values of derivatives for each location in X0

Author(s)

Conversion for sensitivity package by Joseph Guillaume, based on original R code by Oldrich Rakovec. Addition of the varoutput argument by Bertrand Iooss (2020).

References

Rakovec, O., M. C. Hill, M. P. Clark, A. H. Weerts, A. J. Teuling, R. Uijlenhoet (2014), Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models, Water Resour. Res., 50, 1-18

See Also

parameterSets which is used to generate points, sensitivity for other methods in the package

Examples

# 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)
plot(x)

sensitivity documentation built on Sept. 11, 2024, 9:09 p.m.