sobolSmthSpl: Estimation of Sobol' First Order Indices with B-spline...

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

Estimation of Sobol' First Order Indices with B-spline Smoothing

Description

Determines the Si coefficient for singular parameters through B-spline smoothing with roughness penalty.

Usage

	sobolSmthSpl(Y, X)

Arguments

Y	vector of model responses.
X	matrix having as rows the input vectors corresponding to the responses in Y.

Details

WARNING: This function can give bad results for reasons that have not been yet investigated.

Value

sobolSmthSpl returns a list of class "sobolSmthSpl" containing the following components:

call	the matched call.
X	the provided input matrix.
Y	the provided matrix of model responses.
S	a matrix having the following columns: Si (the estimated first order Sobol' indices), Si.e (the standard errors for the estimated first order Sobol' indices) and q0.05 (the 0.05 quantiles assuming for the Si indices Normal distributions centred on the Si estimates and with standard deviations the calculated standard errors)

Author(s)

Filippo Monari

References

Saltelli, A; Ratto, M; Andres, T; Campolongo, F; Cariboni, J; Gatelli, D; Saisana, M & Tarantola, S. Global Sensitivity Analysis: The Primer Wiley-Interscience, 2008

M Ratto and A. Pagano, 2010, Using recursive algorithms for the efficient identification of smoothing spline ANOVA models, Advances in Statistical Analysis, 94, 367–388.

See Also

sobol, sobolEff, sobolGP

Examples

	X = matrix(runif(5000), ncol = 10)
	Y = sobol.fun(X)
	sa = sobolSmthSpl(Y, X)
	plot(sa)

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