window

This function trim the sequences of model parameters of a DGP emulator
that are generated during the 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) <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 sequences.</dd>
<dt>end</dt>
<dd>the last iteration after which all iterations are trimmed from the sequences.
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 sequences.
Defaults to 1.</dd></dl>

Arguments

Trim the sequences of model parameters of 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 sequences.</dd>


<dt>end</dt>
<dd>the last iteration after which all iterations are trimmed from the sequences.
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 sequences.
Defaults to 1.</dd>

</dl>

window: Trim the sequences of model parameters of a DGP emulator

Description

Usage

Value

Arguments

Details

Examples