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

Gaussian_hessianCC(XX, X, Z, Kinv, mu_hat, theta)

<table summary="R argblock">
<tr valign="top">
<td><code>XX</code></td>
<td>
point to find Hessian at
</td>
</tr>
<tr valign="top">
<td><code>X</code></td>
<td>
matrix of data points
</td>
</tr>
<tr valign="top">
<td><code>Z</code></td>
<td>
matrix of output
</td>
</tr>
<tr valign="top">
<td><code>Kinv</code></td>
<td>
inverse of correlation matrix
</td>
</tr>
<tr valign="top">
<td><code>mu_hat</code></td>
<td>
mean estimate
</td>
</tr>
<tr valign="top">
<td><code>theta</code></td>
<td>
correlation parameters
</td>
</tr>
</table>

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

Gaussian_hessianCC

Description

Usage

Arguments

Value

GauPro

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`XX`	point to find Hessian at
`X`	matrix of data points
`Z`	matrix of output
`Kinv`	inverse of correlation matrix
`mu_hat`	mean estimate
`theta`	correlation parameters