tgp (version 1.0-1)

tgp.get.partitions: Get partition of data from maximum a' posteriori tree

Description

Partition data according to the maximum a' posteriori (MAP) tree contained in a "tgp" object.

Usage

tgp.get.partitions(X, out)

Arguments

X

data.frame, matrix, or vector of inputs X with the same dimension of out$X, i.e., dim(X)[2] == dim(out$X)[2]

out

"tgp" class object which is the output of one the model functions with tree support (e.g. btgpllm, btgp, btl

Value

• Output is a list of data.frames containing the inputs X contained in each region of the partition of the MAP tree in the "tgp" class object out

References

Gramacy, R. B., Lee, H. K. H., & Macready, W. (2004). Parameter space exploration with Gaussian process trees. ICML (pp. 353--360). Omnipress & ACM Digital Library.

Gramacy, R. B., Lee, H. K. H., & Macready, W. (2005). Adaptive Exploration of Computer Experiment Parameter Spaces. submitted to JCGS, available as UCSC Technical Report ams2005-16 http://www.ams.ucsc.edu/reports/trview.php?content=view&name=ams2005-16

http://people.ucsc.edu/~boobles/tgp.php

See Also

tgp.design

Examples

#
# 2-d Exponential data
#

# 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) 
tgp.trees(out)

# find a treed sequential D-Optimal design 
# with 10 more points
Xcand.parts <- tgp.get.partitions(Xcand, out)