scaleDesign {DiceDesign} R Documentation

## 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)

### 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

### 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

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)

[Package DiceDesign version 1.9 Index]