Returns an element related to an integral of a derivative of the desired kernel. See references for details.

internal

The active subspace method is a sensitivity analysis technique that finds important linear combinations of input variables for a simulator. This package provides functions allowing estimation of the active subspace without gradient information using Gaussian processes as well as sequential experimental design tools to minimize the amount of data required to do so. Implements Wycoff et al. (JCGS, 2021) <doi:10.48550/arXiv.1907.11572>.

Nathan Wycoff

activegp

Gaussian Process Based Design and Analysis for the Active
Subspace Method

d1 function

<dl><dt>X</dt>
<dd>The design matrix</dd>
<dt>x</dt>
<dd>The point at which to evaluate.</dd>
<dt>sigma</dt>
<dd>The error variance of the model.</dd>
<dt>type</dt>
<dd>A string, one of "Gaussian", "Matern5_2", and "Matern3_2" indicating the covariance kernel to use.</dd></dl>

Arguments

Get Integerodifferential Quantities — d1

<dl>

<dt>X</dt>
<dd>The design matrix</dd>


<dt>x</dt>
<dd>The point at which to evaluate.</dd>


<dt>sigma</dt>
<dd>The error variance of the model.</dd>


<dt>type</dt>
<dd>A string, one of "Gaussian", "Matern5_2", and "Matern3_2" indicating the covariance kernel to use.</dd>

</dl>

d1: Get Integerodifferential Quantities

Description

Usage

Value

Arguments

References