exp2d.rand {tgp}R Documentation

Randomly subsampled 2-d Exponential Data

Description

A Random subsample of data(exp2d)

Usage

exp2d.rand(n1 = 50, n2 = 30)

Arguments

n1 Number of samples from the first, interesting, quadrant
n2 Number of samples from the other three, uninteresting, quadrants

Details

Data is subsampled without replacement from data(exp2d). Of the n1 + n2 >= 441 input/response pairs X,Z, n1 are taken from the first quadrant, i.e., where the response is interesting, and the remaining n1 are taken from the other three quadrant. The remaining 441 - (n1 + n2) are treated as predictive locations

Value

Output is a list with entries:

X 2-d data.frame with n1 + n2 input locations
Z Numeric vector describing the responses (with noise) at the X input locations
Ztrue Numeric vector describing the true responses (without noise) at the X input locations
XX 2-d data.frame containing the remaining 441 - (n1 + n2) input locations
ZZ Numeric vector describing the responses (with noise) at the XX predictive locations
ZZtrue Numeric vector describing the responses (without noise) at the XX predictive locations

Note

This data is used in the examples of the functions listed above in the “See Also” section, below

Author(s)

Robert B. Gramacy rbgramacy@ams.ucsc.edu

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. (2005). Gaussian Processes and Limiting Linear Models. available as UCSC Technical Report ams2005-17

http://www.ams.ucsc.edu/~rbgramacy/tgp.php

See Also

exp2d, tgp, bgpllm, btlm, blm, bgp, btgpllm, bgp

Examples

# random data
ed <- exp2d.rand()

# higher span = 0.5 required because the data is sparse
# and was generated randomly
ed.g <- interp.loess(ed$X[,1], ed$X[,2], ed$Z, span=0.5)

# perspective plot, and plot of the input (X) locations
par(mfrow=c(1,2), bty="n")
persp(ed.g, main="loess surface", theta=-30, phi=20,
      xlab="X[,1]", ylab="X[,2]", zlab="Z")
plot(ed$X, main="Randomly Subsampled Inputs")

[Package tgp version 1.1-5 Index]