# exp2d

##### 2-d Exponential Data

A 2-dimensional data set that can be used to validate non-stationary models.

##### Usage

`data(exp2d)`

##### Details

The true response is evaluated as
$$Z(X)=x_1 * \exp(x_1^2-x_2^2).$$
Zero-mean normal noise
with `sd=0.001`

has been added to the true response

##### Note

This data is used in the examples of the functions listed below in
the “See Also” section via the `exp2d.rand`

function

##### Format

A `data frame`

with 441 observations on the following 4 variables.

`X1`

Numeric vector describing the first dimension of

`X`

inputs`X2`

Numeric vector describing the second dimension of

`X`

inputs`Z`

Numeric vector describing the response

`Z(X)+N(0,sd=0.001)`

`Ztrue`

Numeric vector describing the true response

`Z(X)`

, without noise

##### References

Gramacy, R. B. (2020) *Surrogates: Gaussian Process Modeling,
Design and Optimization for the Applied Sciences*. Boca Raton,
Florida: Chapman Hall/CRC.
https://bobby.gramacy.com/surrogates/

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).
https://www.jstatsoft.org/v19/i09

Robert B. Gramacy, Matthew Taddy (2010). *Categorical Inputs,
Sensitivity Analysis, Optimization and Importance Tempering with tgp
Version 2, an R Package for Treed Gaussian Process Models.*
Journal of Statistical Software, **33**(6), 1--48.
https://www.jstatsoft.org/v33/i06/.

Gramacy, R. B., Lee, H. K. H. (2008).
*Bayesian treed Gaussian process models with an application
to computer modeling*. Journal of the American Statistical Association,
103(483), pp. 1119-1130. Also available as ArXiv article 0710.4536
https://arxiv.org/abs/0710.4536

##### See Also

`exp2d.rand`

, `exp2d.Z`

,
`btgp`

, and other `b*`

functions

*Documentation reproduced from package tgp, version 2.4-17, License: LGPL*