exp2d.Z {tgp}R Documentation

Random Z-values for 2-d Exponential Data

Description

Evaluate the functional (mean) response for the 2-d exponential data (truth) at the X inputs, and randomly sample noisy Z–values having normal error with standard deviation provided.

Usage

exp2d.Z(X, sd=0.001)

Arguments

X Must be a matrix or a data.frame with two columns describing input locations
sd Standard deviation of iid normal noise added to the responses

Details

The response is evaluated as

Z(X) = X1 * exp(-X1^2 -X2^2),

thus creating the outputs Z and Ztrue. Zero-mean normal noise with sd=0.001 is added to the responses Z and ZZ

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

Author(s)

Robert B. Gramacy, rbgramacy@ams.ucsc.edu
Matt Taddy, taddy@ams.ucsc.edu

References

Gramacy, R. B. (2007). tgp: An R Package for Bayesian Nonstationary, Semiparametric Nonlinear Regression and Design by Treed Gaussian Process Models. Journal of Statistical Software, 19(9). http://www.jstatsoft.org/v19/i09

Gramacy, R. B., Lee, H. K. H. (2007). Bayesian treed Gaussian process models with an application to computer modeling Journal of the American Statistical Association, to appear. Also available as as ArXiv article 0710.4536 http://arxiv.org/abs/0710.4536

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")

[Package tgp version 2.1-4 Index]