tgp (version 1.1-11)

exp2d.Z: Random Z-values for 2-d Exponential Data

Description

A Random subsample of data(exp2d), or Latin Hypercube sampled data evaluated similarly

Usage

exp2d.Z(X, sd=0.001)

Arguments

X

Must be a matrix or a data.frame with two colmuns describing input locations

sd

Standard deviation of iid normal noise added to the resoponses

Value

• Output is a data.frame with columns:
• 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

Details

The response is evaluated as $$Z(X)=x_1 * \exp(x_1^2-x_2^2).$$ thus creating the outputs Ztruth and ZZtruth. Zero-mean normal noise with sd=0.001 is added to the responses Z and ZZ

References

Gramacy, R. B., Lee, H. K. H. (2006). Bayesian treed Gaussian process models. Available as UCSC Technical Report ams2006-01.

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

See Also

exp2d, exp2d.rand

Examples

N <- 20
x <- seq(-2,6,length=N)
X <- expand.grid(x, x)
Zdata <- exp2d.Z(X)
persp(x,x,matrix(Zdata$Ztrue, nrow=N), theta=-30, phi=20,
      main="Z true", xlab="x1", ylab="x2", zlab="Ztrue")