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.
numeric vector containing the values for factor 1.
numeric vector containing the values for factor 2.
numeric vector containing the values for factor 3.
logical value deciding whether noise should be added or not. Default setting is ‘FALSE’.
factor 1 is best within [40, 250]; factor 2 within [90, 240]
simProc returns a numeric value within the range [0,1].
For an example in context which shows the usage of the function
please read the vignette for the package
qualityTools at http://www.r-qualitytools.org/html/Improve.html
Thomas Roth email@example.com
facDesign for 2^k factorial designs
rsmDesign for response surface designs
fracDesign for fractional factorial design
1 2 3
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