CGGP_internal_MSEpredcalc

Calculate MSE prediction along a single dimension

Run computer experiments using the adaptive composite grid
algorithm with a Gaussian process model.
The algorithm works best when running an experiment that can evaluate thousands
of points from a deterministic computer simulation.
This package is an implementation of a forthcoming paper by Plumlee,
Erickson, Ankenman, et al. For a preprint of the paper,
contact the maintainer of this package.

Collin Erickson

CGGP

Composite Grid Gaussian Processes

Matthew Plumlee

CGGP_internal_MSEpredcalc function

<dl><dt>xp</dt>
<dd>Points at which to calculate MSE</dd>
<dt>xl</dt>
<dd>Levels along dimension, vector???</dd>
<dt>theta</dt>
<dd>Correlation parameters</dd>
<dt>CorrMat</dt>
<dd>Function that gives correlation matrix for vectors of 1D points.</dd></dl>

Arguments

Calculate MSE prediction along a single dimension — CGGP_internal_MSEpredcalc

<dl>

<dt>xp</dt>
<dd>Points at which to calculate MSE</dd>


<dt>xl</dt>
<dd>Levels along dimension, vector???</dd>


<dt>theta</dt>
<dd>Correlation parameters</dd>


<dt>CorrMat</dt>
<dd>Function that gives correlation matrix for vectors of 1D points.</dd>

</dl>

CGGP_internal_MSEpredcalc: Calculate MSE prediction along a single dimension

Description

Usage

Value

Arguments

Examples