Fits a Gaussian process model to data. Gaussian processes
are commonly used in computer experiments to fit an interpolating model.
The model is stored as an 'R6' object and can be easily updated with new
data. There are options to run in parallel (not for Windows), and 'Rcpp'
has been used to speed up calculations. Other R packages that perform
similar calculations include 'laGP', 'DiceKriging', 'GPfit', and 'mlegp'.

Gaussian Process Fitting

package-ubuntu-20.04-r-4.0.5#cran#GauPro-0.2.4

Correlation Gaussian matrix gradient in C using Armadillo

<table summary="R argblock">
<tr valign="top">
<td><code>XX</code></td>
<td>
Matrix XX to get gradient for
</td>
</tr>
<tr valign="top">
<td><code>X</code></td>
<td>
Matrix X GP was fit to
</td>
</tr>
<tr valign="top">
<td><code>theta</code></td>
<td>
Theta vector
</td>
</tr>
<tr valign="top">
<td><code>s2</code></td>
<td>
Variance parameter
</td>
</tr>
</table>

3-dim array of correlation derivative

# corr_gauss_dCdX(matrix(c(1,0,0,1),2,2),c(1,1))

package-ubuntu-20.04-r-4.0.5#cran#GauPro-0.2.4#docs#corr_gauss_dCdX

corr_gauss_dCdX

Description

Usage

Arguments

Value

Examples

GauPro

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`XX`	Matrix XX to get gradient for
`X`	Matrix X GP was fit to
`theta`	Theta vector
`s2`	Variance parameter