#
# 2-d Exponential data
# (This example is based on random data.
# It might be fun to run it a few times)
#
# get the data
exp2d.data <- exp2d.rand()
X <- exp2d.data$X; Z <- exp2d.data$Z
Xcand <- exp2d.data$XX
# fit treed GP LLM model to data w/o prediction
# basically just to get MAP tree (and plot it)
out <- btgpllm(X=X, Z=Z, pred.n=FALSE, BTE=c(2000,3000,2))
tgp.trees(out)
# find a treed sequential D-Optimal design
# with 10 more points
Xcand.parts <- partition(Xcand, out)
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