Kernel.class

See the function <code><a rd-options="" href="/link/model?package=CaliCo&version=0.1.1" data-mini-rdoc="CaliCo::model">model</a></code> which produces an instance of this class

datasets

Calibration of every computational code. It uses a Bayesian framework to rule the estimation. With a new data set, the prediction will create a prevision set taking into account the new calibrated parameters. The choices between several models is also available. The methods are described in the paper Carmassi et al. (2018) <arXiv:1801.01810>.

Mathieu Carmassi

CaliCo

Code Calibration in a Bayesian Framework

Kernel.class function

An object of class <code>R6ClassGenerator</code> of length 24.

Format

<dl class="dl-horizontal">
<dt><code>code</code></dt><dd>a function which takes in entry X and theta</dd></dl><dt><code>X</code></dt><dd>the matrix of the forced variables</dd><dt><code>var</code></dt><dd>the variance for the covariance function</dd><dt><code>psi</code></dt><dd>the scale vector of correlation length</dd><dt><code>n</code></dt><dd>number of experiments</dd><dt><code>Kernel.type</code></dt><dd>the chosen form of covariance</dd><dt><code>Cov</code></dt><dd>the covariance</dd>

Fields

See the function <code><a rd-options='' href='model'>model</a></code> which produces an instance of this class

Kernel.class: A Reference Class to generates differents model objects

Description

Usage

Arguments

Format

Fields