facDesign: facDesign

In r6qualitytools: R6-Based Statistical Methods for Quality Science

facDesign

Description

Generates a 2^k full factorial design.

Usage

facDesign(
  k = 3,
  p = 0,
  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. For further information see fracDesign and fracChoose. By default p is set to '0'.
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'. Blocking is only performed for k greater 2.
centerCube	Numeric value giving the number of centerpoints within the 2^k design. By default centerCube is set to '0'.
random.seed	Numeric value for setting the random seed for reproducibility.

Value

The function facDesign returns an object of class facDesign.c.

See Also

fracDesign, fracChoose, rsmDesign, pbDesign, taguchiDesign

Examples

# Example 1
vp.full <- facDesign(k = 3)
vp.full$.response(rnorm(2^3))
vp.full$summary()

# Example 2
vp.rep <- facDesign(k = 2, replicates = 3, centerCube = 4)
vp.rep$names(c("Name 1", "Name 2"))
vp.rep$unit(c("min", "F"))
vp.rep$lows(c(20, 40, 60))
vp.rep$highs(c(40, 60, 80))
vp.rep$summary()

# Example 3
dfac <- facDesign(k = 3, centerCube = 4)
dfac$names(c('Factor 1', 'Factor 2', 'Factor 3'))
dfac$names()
dfac$lows(c(80, 120, 1))
dfac$lows()
dfac$highs(c(120, 140, 2))
dfac$highs()
dfac$summary()

r6qualitytools documentation built on Oct. 4, 2024, 1:09 a.m.