modelCall-class

User reminder of the <a rd-options="funGp" href="/link/fgpm?package=funGp&version=0.2.1&to=funGp" data-mini-rdoc="funGp::fgpm">fgpm</a> function call.

Construction and smart selection of Gaussian process models
with emphasis on treatment of functional inputs. This package
offers: (i) flexible modeling of functional-input regression
problems through the fairly general Gaussian process model; (ii)
built-in dimension reduction for functional inputs; (iii)
heuristic optimization of the structural parameters of the model
(e.g., active inputs, kernel function, type of distance).
Metamodeling background is provided in
Betancourt et al. (2020) <doi:10.1016/j.ress.2020.106870>.
The algorithm for structural parameter optimization is described
in <https://hal.archives-ouvertes.fr/hal-02532713>.

Jose Betancourt

funGp

Gaussian Process Models for Scalar and Functional Inputs

Fran<c3><a7>ois Bachoc

Thierry Klein

Deborah Idier

Jeremy Rohmer

modelCall-class function

<dl class="dl-horizontal">
<dt><code>string</code></dt><dd>Object of class <code>"character"</code>. User call reminder in string format.</dd>
</dl>

Slots

User reminder of the <a rd-options='funGp' href='fgpm'>fgpm</a> function call.

modelCall-class: S4 class for calls to the fgpm function in funGp

Description

Arguments

Slots