This R package provides a class that generates experiment sFFLHD designs. Sequential full factorial-based Latin hypercube design were created by Duan, Ankenman, Sanchez, and Sanchez (2015, Technometrics).
To create a new design you use the function
sFFLHD$new and must give in the number of dimensions,
D, and the batch size/number of levels per factor,
L. An example is shown below (the last line can be repeated when run in console to see how new batches are added).
library(sFFLHD) #> Loading required package: DoE.base #> Loading required package: grid #> Loading required package: conf.design #> #> Attaching package: 'DoE.base' #> The following objects are masked from 'package:stats': #> #> aov, lm #> The following object is masked from 'package:graphics': #> #> plot.design #> The following object is masked from 'package:base': #> #> lengths set.seed(0) s <- sFFLHD$new(D=2,L=3) plot(s$get.batch(),xlim=0:1,ylim=0:1,pch=19) abline(h=(0:(s$Lb))/s$Lb,v=(0:(s$Lb))/s$Lb,col=3);points(s$get.batch(),pch=19)
By default the new points are selected using maximin distance optimization to spread them out. This is why points will end up near corners. This option will slow down the code a little but generally not noticeably compared to what the design is used for. If set to
FALSE then the points are randomly placed within their small grid box.