print_uncertainty: Prints a measure of uncertainty for a function of any dimension.

Description

This function prints in the whole input domain the value of a given measure of uncertainty. Possible measures are "pn" (the probability of excursion) and measures specific to a sampling criterion: "sur", "timse" and "imse". This function can be used to print relevant outputs after having used the function EGI.

Usage

print_uncertainty(model, T, type = "pn", ...)

Arguments

model

Kriging model of km class.

Target value (scalar).

type

Type of uncertainty that the user wants to print. Possible values are "pn" (probability of excursion), or "sur", "imse", "timse", "vorob" if we print a measure of uncertainty corresponding to one criterion.

…

Other arguments of the function print_uncertainty_1d, 2d or nd.

Value

the integrated uncertainty

References

Bect J., Ginsbourger D., Li L., Picheny V., Vazquez E. (2010), Sequential design of computer experiments for the estimation of a probability of failure, Statistics and Computing, pp.1-21, 2011, http://arxiv.org/abs/1009.5177

Examples

Run this code

# NOT RUN {
#print_uncertainty

set.seed(8)
N <- 9 #number of observations
T <- 80 #threshold
testfun <- branin
lower <- c(0,0)
upper <- c(1,1)

#a 9 points initial design
design <- data.frame( matrix(runif(2*N),ncol=2) )
response <- testfun(design)

#km object with matern3_2 covariance
#params estimated by ML from the observations
model <- km(formula=~., design = design, 
	response = response,covtype="matern3_2")

#you could do many plots, but only one is run here
print_uncertainty(model=model,T=T,main="probability of excursion",type="pn")
#print_uncertainty(model=model,T=T,main="Vorob'ev uncertainty",type="vorob")
#print_uncertainty(model=model,T=T,main="imse uncertainty",type="imse")
#print_uncertainty(model=model,T=T,main="timse uncertainty",type="timse")
#print_uncertainty(model=model,T=T,main="sur uncertainty",type="sur")
#print_uncertainty(model=model,T=T,main="probability of excursion",type="pn",
#vorobmean=TRUE)
# }