This is a function to simulate a black box process for teaching the use of designed experiments.
The optimal factor settings can be found using a sequential assembly strategy i.e. apply a 2^k factorial design first,
calculate the path of the steepest ascent, again apply a 2^k factorial design and augment a star portion
to find the optimal factor settings. Of course, other strategies are possible.
Usage
simProc(x1, x2, x3, noise = TRUE)
Arguments
- x1
numeric vector containing the values for factor 1.
- x2
numeric vector containing the values for factor 2.
- x3
numeric vector containing the values for factor 3.
- noise
logical value deciding whether noise should be added or not. Default setting is TRUE.
Value
simProc returns a numeric value within the range [0,1].
Examples
simProc(120, 140, 1)
#> [1] 0.4777199
simProc(120, 220, 1)
#> [1] 0.00209724
simProc(160, 140, 1)
#> [1] 0.2638334