unscaleDesign: Unscale a Design

In DiceDesign: Designs of Computer Experiments

Unscale a Design

Description

This function unscales the values of a scaled design (values in [0,1]). The unscaling can be made by the inverse Rosenblatt transformation (by applying the empirical quantile function given by another design) or by translating the design from maximum and minimum values (given for each variable).

Usage

unscaleDesign(design, min=NULL, max=NULL, uniformize=FALSE, InitialDesign=NULL)

Arguments

design	a matrix (or a data.frame) corresponding to the design of experiments to unscale
min	the vector of minimal bounds of each design variable
max	the vector of maximal bounds of each design variable
uniformize	boolean: TRUE to use the inverse Rosenblatt transformation (the min and max vectors are useless in this case). If FALSE (default value), the translation from max and min values is applied
InitialDesign	If the inverse Rosenblatt transformation is applied (uniformize = TRUE): a matrix (or a data.frame) corresponding to the design which gives the empirical quantiles

Value

A list containing:

design	the unscaled design
min	the vector of minimal bounds that has been used
max	the vector of maximal bounds that has been used
uniformize	the value of this boolean argument

Author(s)

B. Iooss

Examples

  d <- 2
  n <- 100
  x <- matrix(rnorm(d*n), ncol=d)
  xscale <- scaleDesign(x, uniformize=TRUE)
  xunscale1 <- unscaleDesign(xscale$design, uniformize=TRUE, InitialDesign=x)
  xunscale2 <- unscaleDesign(xscale$design, 
  min=c(min(x[,1]), min(x[,2])), max = c(max(x[,1]), max(x[,2])))
  par(mfrow=c(2,2))
  plot(x) ; plot(xscale$design)
  plot(xunscale1$design) ; plot(xunscale2$design) 

DiceDesign documentation built on May 29, 2024, 10:35 a.m.