exp2d

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

datasets

datagen

Bayesian nonstationary, semiparametric nonlinear regression
and design by treed Gaussian processes (GPs) with jumps to the limiting
linear model (LLM).  Special cases also implemented include Bayesian
linear models, CART, treed linear models, stationary separable and
isotropic GPs, and GP single-index models.  Provides 1-d and 2-d plotting functions
(with projection and slice capabilities) and tree drawing, designed for
visualization of tgp-class output.  Sensitivity analysis and
multi-resolution models are supported. Sequential experimental
design and adaptive sampling functions are also provided, including ALM,
ALC, and expected improvement.  The latter supports derivative-free
optimization of noisy black-box functions.

Robert Gramacy

Bayesian Treed Gaussian Process Models

exp2d function

A <code>data frame</code> with 441 observations on the following 4 variables.<dl class="dl-horizontal">
 <dt><code>X1</code></dt><dd>Numeric vector describing the first dimension of <code>X</code> inputs</dd>
 <dt><code>X2</code></dt><dd>Numeric vector describing the second dimension of <code>X</code> inputs</dd>
 <dt><code>Z</code></dt><dd>Numeric vector describing the response <code>Z(X)+N(0,sd=0.001)</code></dd>
 <dt><code>Ztrue</code></dt><dd>Numeric vector describing the true response <code>Z(X)</code>,
 	without noise</dd>
 </dl>

Format

2-d Exponential Data — exp2d

A <code>data frame</code> with 441 observations on the following 4 variables.<dl class='dl-horizontal'>
 <dt><code>X1</code></dt><dd>Numeric vector describing the first dimension of <code>X</code> inputs</dd>
 <dt><code>X2</code></dt><dd>Numeric vector describing the second dimension of <code>X</code> inputs</dd>
 <dt><code>Z</code></dt><dd>Numeric vector describing the response <code>Z(X)+N(0,sd=0.001)</code></dd>
 <dt><code>Ztrue</code></dt><dd>Numeric vector describing the true response <code>Z(X)</code>,
 	without noise</dd>
 </dl>

exp2d: 2-d Exponential Data

Description

Usage

Arguments

Format

Details

References

See Also