hsicSA: Hilbert-Schmidt Independence Criterion Sensitivity Analysis

In ppernot/rgumlib: Uncertainty Propagation (GUM & GUM-Supp1) and Sensitivity Analysis

Description

Uses Monte Carlo sample to generate Hilbert-Schmidt Independence Criterion based SA indices

Usage

hsicSA(X, Y, budgetTable = TRUE, silent = FALSE)

Arguments

X	A MxN matrix of M values for N input variables.
Y	A vector of values corresponding to X.
budgetTable	Flag to compute the budget table.
silent	Flag to run without printout.

Value

A list containing:

hs	(vector) HSIC sensitivity indices
budget	(dataframe) VG budget table, mostly to be printed

References

Da Veiga S. (2015), Global sensitivity analysis with dependence measures, J. Stat. Comp. Sim., 85:1283-1305.

Examples

fExpr = expression(x1+x2)
x.mu = c(1,1); names(x.mu)=c('x1','x2')
x.u = c(0.1,0.1); names(x.u)=c('x1','x2')
x.pdf = c('unif','triangle'); names(x.pdf)=c('x1','x2')
S = gumS1(fExpr,x.mu,x.u,x.pdf,x.df=NULL,nrunMax=1000)
hsicSA(S$X,S$Y,silent=TRUE)

ppernot/rgumlib documentation built on May 25, 2019, 11:24 a.m.