DiceDesign (version 1.10)

scaleDesign: Scale a Design

Description

This function scales the values of the design points to values comprised in [0,1]. The scaling can be made by the Rosenblatt transformation (uniformization by applying the empirical cumulative distribution function) or by translating the design from maximum and minimum values (given for each variable).

Usage

scaleDesign(design, min=NULL, max=NULL, uniformize=FALSE)

Value

A list containing:

design

the scaled 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

InitialDesign

the starting design

Arguments

design

a matrix (or a data.frame) corresponding to the design of experiments to scale

min

the vector of minimal bounds of each design variable. If not given, the minimal value of each variable is taken

max

the vector of maximal bounds of each design variable. If not given, the maximal value of each variable is taken

uniformize

boolean: TRUE to use the 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

Author

B. Iooss

Examples

  d <- 2
  n <- 100
  x <- matrix(rnorm(d*n), ncol=d)
  xscale1 <- scaleDesign(x, uniformize=FALSE)
  xscale2 <- scaleDesign(x, uniformize=TRUE)
  par(mfrow=c(1,2))
  plot(xscale1$design) ; plot(xscale2$design)