window

This function trims the sequence of hyperparameter estimates within a DGP emulator
generated during training.

Interface to the 'python' package 'dgpsi' for Gaussian process, deep Gaussian process,
and linked deep Gaussian process emulations of computer models and networks using stochastic imputation (SI).
The implementations follow Ming & Guillas (2021) <doi:10.1137/20M1323771> and
Ming, Williamson, & Guillas (2023) <doi:10.1080/00401706.2022.2124311> and
Ming & Williamson (2023) <doi:10.48550/arXiv.2306.01212>. To get started with the package,
see <https://mingdeyu.github.io/dgpsi-R/>.

Deyu Ming

dgpsi

Interface to 'dgpsi' for Deep and Linked Gaussian Process
Emulations

Daniel Williamson

window function

<dl><dt>object</dt>
<dd>an instance of the S3 class <code>dgp</code>.</dd>
<dt>start</dt>
<dd>the first iteration before which all iterations are trimmed from the sequence.</dd>
<dt>end</dt>
<dd>the last iteration after which all iterations are trimmed from the sequence.
Set to <code>NULL</code> to keep all iterations after (including) <code>start</code>. Defaults to <code>NULL</code>.</dd>
<dt>thin</dt>
<dd>the interval between the <code>start</code> and <code>end</code> iterations to thin out the sequence.
Defaults to 1.</dd></dl>

Arguments

Trim the sequence of hyperparameter estimates within a DGP emulator — window

<dl>

<dt>object</dt>
<dd>an instance of the S3 class <code>dgp</code>.</dd>


<dt>start</dt>
<dd>the first iteration before which all iterations are trimmed from the sequence.</dd>


<dt>end</dt>
<dd>the last iteration after which all iterations are trimmed from the sequence.
Set to <code>NULL</code> to keep all iterations after (including) <code>start</code>. Defaults to <code>NULL</code>.</dd>


<dt>thin</dt>
<dd>the interval between the <code>start</code> and <code>end</code> iterations to thin out the sequence.
Defaults to 1.</dd>

</dl>

window: Trim the sequence of hyperparameter estimates within a DGP emulator

Description

Usage

Value

Arguments

Details

Examples