VdgRsm (version 1.4)

cpv: Cuboidal Prediction Variance

Description

Create a Variance Dispesion Graph for a response surface design in a cuboidal region.

Usage

cpv(design.matrix, design.matrix.2 = NULL, des.names = c("Design 1","Design 2"),
    add.pts = TRUE)

Arguments

design.matrix, design.matrix.2

Data frames of design points to be compared in coded or uncoded units. There should be one column for each factor in the design, and one row for each run in the design. The maximum number of factors is 6. If the number of factor is more than 4, only one d

add.pts

Generate scaled prediction variances of random design points in the VDG. By default add.pts = TRUE.

des.names

A vector of descriptive names for designs in character strings.

Value

• cpv is called to generate a Variance Dispersion Graph when the number of factors k = 2, 3, or 4 and to generate side-by-side boxplots for k = 5 and 6. In the former case, a table of the minimum, maximum, and average of scaled prediction variances is also produced.

Examples

CCD1<- gen.CCD(n.vars = 3, n.center = 2, alpha = 1)
CCD2<- gen.CCD(n.vars = 3, n.center = 5, alpha = 1)
cpv(CCD1, CCD2, des.names = c("CCD with nc=2", "CCD with nc=5"), add.pts = FALSE)