qualityTools (version 1.55)

fracDesign: fracDesign

Description

Generates a 2^k full- or fractional factorial design.

Usage

fracDesign(k = 3, p = 0, gen = NULL, replicates = 1, blocks = 1, centerCube = 0, random.seed = 1234)

Arguments

k

numeric value giving the number of factors. By default k is set to ‘3’.

p

numeric integer between ‘0’ and ‘7’. p is giving the number of additional factors in the response surface design by aliasing effects. A 2^k-p factorial design will be generated and the generators of the standard designs available in fracChoose() will be used. By default p is set to ‘0’. Any other value will cause the function to omit the argument gen given by the user and replace it by the one out of the table of standard designs (see: fracChoose()). Replicates and blocks can be set anyway!

gen

one or more defining relations for a fractional factorial design. By default gen is set to ‘NULL’.

replicates

numeric value giving the number of replicates per factor combination. By default replicates is set to ‘1’.

blocks

numeric value giving the number of blocks. By default blocks is set to ‘1’.

centerCube

numeric value giving the number of centerpoints within the 2^k design. By default centerCube is set to ‘0’.

random.seed

seed for randomization of the design

Value

returns an object of class facDesign.

Details

fracDesign generates 2^k full- or fractional factorial designs.

See Also

facDesign fracChoose pbDesign rsmDesign taguchiDesign http://www.r-qualitytools.org/html/Improve.html

Examples

#returns a 2^3 full factorial design
vp.full = facDesign(k = 3)       
#design in 2 blocks                           
vp.full = blocking(vp.full, 2)   
#generate some random response                           
response(vp.full) = rnorm(2^3)   
#summary of the full factorial design (especially no defining relation)                           
summary(vp.full)                                           

#returns a 2^4-1 fractional factorial design. Factor D will be aliased with
vp.frac = fracDesign(k = 4, gen = "D=ABC") 
#the three-way-interaction ABC (i.e. I = ABCD)                 
response(vp.frac) = rnorm(2^(4-1))    
#summary of the fractional factorial design                      
summary(vp.frac)                                            

#returns a full factorial design with 3 replications per factor combination 
#and 4 center points
vp.rep = fracDesign(k = 3, replicates = 3, centerCube = 4)  
#summary of the replicated fractional factorial Design
summary(vp.rep)