Rn1_CvM

<p>Implements the "interface" Rn1_statistic</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

Rn1_CvM function

<p><code>bootGOF::Rn1_statistic</code> -&gt; <code>Rn1_CvM</code></p>

Super class


<div class="section" id="public-methods">
<h3>Public methods</h3><p></p><p><ul>
<li><p><a href="/link/Rn1_CvM%24calc_statistic()?package=bootGOF&version=0.1.0" data-mini-rdoc="bootGOF::Rn1_CvM$calc_statistic()"><code>Rn1_CvM$calc_statistic()</code></a></p></li>
<li><p><a href="/link/Rn1_CvM%24clone()?package=bootGOF&version=0.1.0" data-mini-rdoc="bootGOF::Rn1_CvM$clone()"><code>Rn1_CvM$clone()</code></a></p></li>
</ul></p><p></p></div><p><details open><summary>Inherited methods</summary>
<ul>
</ul>
</details></p><p><hr>
<a id="method-calc_statistic"></a></p><div class="section" id="method-calc-statistic-">
<h3>Method <code>calc_statistic()</code></h3>
<p>calculates the calculates the Cramer-von-Mises
  statistic</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>Rn1_CvM$calc_statistic(Rn1)</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>Rn1</code></dt>
<dd><p>see Rn1_statistic</p></dd></dl></div></p><p>
</p><p></p>

<div class="section" id="returns">
<h4>Returns</h4>
<p>see Rn1_statistic</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>Rn1_CvM$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

Cramer-von-Mises-statistic for marked empirical
  process — Rn1_CvM


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

<ul>
<li><p><a href='#method-calc_statistic'><code>Rn1_CvM$calc_statistic()</code></a></p></li>
<li><p><a href='#method-clone'><code>Rn1_CvM$clone()</code></a></p></li>
</ul>

</div><p><details open ><summary>Inherited methods</summary>
<ul>
</ul>
</details>

<hr>
<a id="method-calc_statistic"></a></p><div class='section' id='method-calc-statistic-'>
<h3>Method <code>calc_statistic()</code></h3>
<p>calculates the calculates the Cramer-von-Mises
  statistic</p><div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>Rn1_CvM$calc_statistic(Rn1)</code></pre><p></div></p>
</div>

<div class='section' id='arguments'>
<h4>Arguments</h4>
<p><div class="arguments"></p><dl>
<dt><code>Rn1</code></dt>
<dd><p>see Rn1_statistic</p></dd>


</dl><p></div></p>
</div>
<div class='section' id='returns'>
<h4>Returns</h4>
<p>see Rn1_statistic</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>Rn1_CvM$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>


Rn1_CvM: Cramer-von-Mises-statistic for marked empirical process

Description

Arguments

Super class

Methods

Public methods

Method `calc_statistic()`

Usage

Arguments

Returns

Method `clone()`

Usage

Arguments

Description

Arguments

Super class

Methods

Public methods

Method calc_statistic()

Usage

Arguments

Returns

Method clone()

Usage

Arguments

Method `calc_statistic()`

Method `clone()`