GOF_glm_trainer

<p>refits an object of class "glm" to a new data set</p>

Bootstrap based goodness-of-fit tests. It allows
to perform rigorous statistical tests to check if a chosen
model family is correct based on the marked empirical
process. The implemented algorithms are described in
(Dikta and Scheer (2021) <doi:10.1007/978-3-030-73480-0>)
and can be applied
to generalized linear models without any further implementation
effort. As far as certain linearity conditions are fulfilled
the resampling scheme are also applicable beyond generalized
linear models. This is reflected in the software architecture
which allows to reuse the resampling scheme by implementing
only certain interfaces for models that are not supported
natively by the package.

Marsel Scheer

bootGOF

Bootstrap Based Goodness-of-Fit Tests

Gerhard Dikta

GOF_glm_trainer function


<div class="section" id="public-methods">
<h3>Public methods</h3><p></p><p><ul>
<li><p><a href="/link/GOF_glm_trainer%24refit()?package=bootGOF&version=0.1.0" data-mini-rdoc="bootGOF::GOF_glm_trainer$refit()"><code>GOF_glm_trainer$refit()</code></a></p></li>
<li><p><a href="/link/GOF_glm_trainer%24clone()?package=bootGOF&version=0.1.0" data-mini-rdoc="bootGOF::GOF_glm_trainer$clone()"><code>GOF_glm_trainer$clone()</code></a></p></li>
</ul></p><p></p></div><p><hr>
<a id="method-refit"></a></p><div class="section" id="method-refit-">
<h3>Method <code>refit()</code></h3>
<p>see GOF_model_trainer</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>GOF_glm_trainer$refit(model, data)</code></pre><p></p></div><p></p>
</div><p></p><p><div class="section" id="arguments">
<h4>Arguments</h4>
<p><div class="arguments"></div></p><dl>
<dt><code>model</code></dt>
<dd><p>see GOF_model_trainer</p></dd></dl></div></p><p>
<dt><code>data</code></dt>
<dd><p>see GOF_model_trainer</p></dd></p><p>
</p><p></p>

<div class="section" id="returns">
<h4>Returns</h4>
<p>see GOF_model_trainer</p>
</div><p></p><p></p><p><hr>
<a id="method-clone"></a></p><div class="section" id="method-clone-">
<h3>Method <code>clone()</code></h3>
<p>The objects of this class are cloneable with this method.</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>GOF_glm_trainer$clone(deep = FALSE)</code></pre><p></p></div><p></p>
</div><p></p><p><div class="section" id="arguments">
<h4>Arguments</h4>
<p><div class="arguments"></div></p><dl>
<dt><code>deep</code></dt>
<dd><p>Whether to make a deep clone.</p></dd></dl></div></p><p>
</p><p></p>
<p></p><p>
</p>

Methods

Implements the "interface" GOF_model_trainer for
  for generalized linear models — GOF_glm_trainer


<div class='section' id='public-methods'>
<h3>Public methods</h3>

<ul>
<li><p><a href='#method-refit'><code>GOF_glm_trainer$refit()</code></a></p></li>
<li><p><a href='#method-clone'><code>GOF_glm_trainer$clone()</code></a></p></li>
</ul>

</div><p><hr>
<a id="method-refit"></a></p><div class='section' id='method-refit-'>
<h3>Method <code>refit()</code></h3>
<p>see GOF_model_trainer</p><div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>GOF_glm_trainer$refit(model, data)</code></pre><p></div></p>
</div>

<div class='section' id='arguments'>
<h4>Arguments</h4>
<p><div class="arguments"></p><dl>
<dt><code>model</code></dt>
<dd><p>see GOF_model_trainer</p></dd>


<dt><code>data</code></dt>
<dd><p>see GOF_model_trainer</p></dd>


</dl><p></div></p>
</div>
<div class='section' id='returns'>
<h4>Returns</h4>
<p>see GOF_model_trainer</p>
</div>

</div><p><hr>
<a id="method-clone"></a></p><div class='section' id='method-clone-'>
<h3>Method <code>clone()</code></h3>
<p>The objects of this class are cloneable with this method.</p><div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>GOF_glm_trainer$clone(deep = FALSE)</code></pre><p></div></p>
</div>

<div class='section' id='arguments'>
<h4>Arguments</h4>
<p><div class="arguments"></p><dl>
<dt><code>deep</code></dt>
<dd><p>Whether to make a deep clone.</p></dd>


</dl><p></div></p>
</div>

</div>


GOF_glm_trainer: Implements the "interface" GOF_model_trainer for for generalized linear models

Description

Arguments

Methods

Public methods

Method `refit()`

Usage

Arguments

Returns

Method `clone()`

Usage

Arguments

Description

Arguments

Methods

Public methods

Method refit()

Usage

Arguments

Returns

Method clone()

Usage

Arguments

Method `refit()`

Method `clone()`