coordinateProfiles {profExtrema}R Documentation

Coordinate profiles starting from a kriging model

Description

The function coordinateProfiles computes the profile extrema functions for the posterior mean of a Gaussian process and its confidence bounds

Usage

coordinateProfiles(object, threshold, options_full = NULL,
  options_approx = NULL, uq_computations = FALSE, plot_level = 0,
  plot_options = NULL, CI_const = NULL, return_level = 1, ...)

Arguments

object

either a km model or a list containing partial results. If object is a km model then all computations are carried out. If object is a list, then the function carries out all computations to complete the list results.

threshold

the threshold of interest

options_full

an optional list of options for getAllMaxMin, see getAllMaxMin for details.

options_approx

an optional list of options for approxMaxMin, see approxMaxMin for details.

uq_computations

boolean, if TRUE the uq computations for the profile mean are computed.

plot_level

an integer to select the plots to return (0=no plots, 1=basic plots, 2= all plots)

plot_options

an optional list of parameters for plots. See setPlotOptions for currently available options.

CI_const

an optional vector containing the constants for the CI. If not NULL, then profiles extrema for m_n(x) \pm CI_const[i]*s_n(x,x) are computed.

return_level

an integer to select the amount of details returned

...

additional parameters to be passed to coordProf_UQ.

Value

If return_level=1 a list containing

if return_level=2 the same list as above but also including

Author(s)

Dario Azzimonti

Examples

if (!requireNamespace("DiceKriging", quietly = TRUE)) {
stop("DiceKriging needed for this example to work. Please install it.",
     call. = FALSE)
}
# Compute a kriging model from 50 evaluations of the Branin function
# Define the function
g=function(x){
  return(-branin(x))
}
gp_des<-lhs::maximinLHS(20,2)
reals<-apply(gp_des,1,g)
kmModel<-km(design = gp_des,response = reals,covtype = "matern3_2")

threshold=-10

# Compute coordinate profiles on the posterior mean
# Increase multistart and size of designs for more precise results
options_full<-list(multistart=2,heavyReturn=TRUE, Design = replicate(2,seq(0,1,,50)))
init_des<-lhs::maximinLHS(12,2)
options_approx<- list(multistart=2,heavyReturn=TRUE,initDesign=init_des,fullDesignSize=50)
cProfilesMean<-coordinateProfiles(object=kmModel,threshold=threshold,options_full=options_full,
                                  options_approx=options_approx,uq_computations=FALSE,
                                  plot_level=3,plot_options=NULL,CI_const=NULL,return_level=2)
## Not run: 
# Coordinate profiles with UQ with approximate profiles
plot_options<-list(save=FALSE, titleProf = "Coordinate profiles",
                   title2d = "Posterior mean",qq_fill=TRUE)
cProfilesUQ<-coordinateProfiles(object=cProfilesMean,threshold=threshold,options_full=options_full,
                                  options_approx=options_approx,uq_computations=TRUE,
                                  plot_level=3,plot_options=NULL,CI_const=NULL,return_level=2)

# Coordinate profiles with UQ with fully optim profiles
options_full_sims<-list(multistart=4,heavyReturn=TRUE, Design = replicate(2,seq(0,1,,60)))
cProfilesUQ<-coordinateProfiles(object=cProfilesMean,threshold=threshold,options_full=options_full,
                                  options_approx=options_approx,uq_computations=TRUE,
                                  plot_level=3,plot_options=NULL,CI_const=NULL,return_level=2,
                                  options_full_sims=options_full_sims)

## End(Not run)

[Package profExtrema version 0.2.1 Index]