GOF_sim_wild_rademacher

<p>This is a model agnostic resampling class, where
Rademacher random variables are used to add or substract
the residuals from the fitted values.</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_sim_wild_rademacher function


<div class="section" id="public-methods">
<h3>Public methods</h3><p></p><p><ul>
<li><p><a href="/link/GOF_sim_wild_rademacher%24new()?package=bootGOF&version=0.1.0" data-mini-rdoc="bootGOF::GOF_sim_wild_rademacher$new()"><code>GOF_sim_wild_rademacher$new()</code></a></p></li>
<li><p><a href="/link/GOF_sim_wild_rademacher%24resample_y()?package=bootGOF&version=0.1.0" data-mini-rdoc="bootGOF::GOF_sim_wild_rademacher$resample_y()"><code>GOF_sim_wild_rademacher$resample_y()</code></a></p></li>
<li><p><a href="/link/GOF_sim_wild_rademacher%24clone()?package=bootGOF&version=0.1.0" data-mini-rdoc="bootGOF::GOF_sim_wild_rademacher$clone()"><code>GOF_sim_wild_rademacher$clone()</code></a></p></li>
</ul></p><p></p></div><p><hr>
<a id="method-new"></a></p><div class="section" id="method-new-">
<h3>Method <code>new()</code></h3><p></p><p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>GOF_sim_wild_rademacher$new(gof_model_info_extractor)</code></pre><p></p></div></p>
</div><p></p><p><div class="section" id="arguments">
<h4>Arguments</h4>
<p><div class="arguments"></div></p><dl>
<dt><code>gof_model_info_extractor</code></dt>
<dd><p>the info extractor that is used
to derive the residuals and fitted values for resampling.</p></dd></dl></div></p><p>
</p><p></p>
<p></p><p></p><p><hr>
<a id="method-resample_y"></a></p><div class="section" id="method-resample-y-">
<h3>Method <code>resample_y()</code></h3>
<p>a wild bootstrap using Rademacher random
  variables to resample the dependent variable</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>GOF_sim_wild_rademacher$resample_y(model)</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_simulator</p></dd></dl></div></p><p>
</p><p></p>

<div class="section" id="returns">
<h4>Returns</h4>
<p>see GOF_model_simulator</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_sim_wild_rademacher$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_simulator
  in a semi-parametric fashion — GOF_sim_wild_rademacher


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

<ul>
<li><p><a href='#method-new'><code>GOF_sim_wild_rademacher$new()</code></a></p></li>
<li><p><a href='#method-resample_y'><code>GOF_sim_wild_rademacher$resample_y()</code></a></p></li>
<li><p><a href='#method-clone'><code>GOF_sim_wild_rademacher$clone()</code></a></p></li>
</ul>

</div><p><hr>
<a id="method-new"></a></p><div class='section' id='method-new-'>
<h3>Method <code>new()</code></h3>

<div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>GOF_sim_wild_rademacher$new(gof_model_info_extractor)</code></pre><p></div></p>
</div>

<div class='section' id='arguments'>
<h4>Arguments</h4>
<p><div class="arguments"></p><dl>
<dt><code>gof_model_info_extractor</code></dt>
<dd><p>the info extractor that is used
to derive the residuals and fitted values for resampling.</p></dd>


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

</div><p><hr>
<a id="method-resample_y"></a></p><div class='section' id='method-resample-y-'>
<h3>Method <code>resample_y()</code></h3>
<p>a wild bootstrap using Rademacher random
  variables to resample the dependent variable</p><div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>GOF_sim_wild_rademacher$resample_y(model)</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_simulator</p></dd>


</dl><p></div></p>
</div>
<div class='section' id='returns'>
<h4>Returns</h4>
<p>see GOF_model_simulator</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_sim_wild_rademacher$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_sim_wild_rademacher: Implements the "interface" GOF_model_simulator in a semi-parametric fashion

Description

Arguments

Methods

Public methods

Method `new()`

Usage

Arguments

Method `resample_y()`

Usage

Arguments

Returns

Method `clone()`

Usage

Arguments

Description

Arguments

Methods

Public methods

Method new()

Usage

Arguments

Method resample_y()

Usage

Arguments

Returns

Method clone()

Usage

Arguments

Method `new()`

Method `resample_y()`

Method `clone()`