onesample.cdf

<p>Performs statistical inference on population cumulative distribution function.</p>

Implements non-parametric tests from Higgins (2004, ISBN:0534387756), including tests for one sample, two samples, k samples, paired comparisons, blocked designs, trends and association. Built with 'Rcpp' for efficiency and 'R6' for flexible, object-oriented design, the package provides a unified framework for performing or creating custom permutation tests.

Yan Du

LearnNonparam

'R6'-Based Flexible Framework for Permutation Tests

CDF function

<p><code>LearnNonparam::PermuTest</code> -&gt; <code>LearnNonparam::OneSampleTest</code> -&gt; <code>CDF</code></p>

Super classes


<div class="section" id="public-methods">
<h3>Public methods</h3><p></p><p><ul>
<li><p><a href="/link/CDF%24new()?package=LearnNonparam&version=1.2.7" data-mini-rdoc="LearnNonparam::CDF$new()"><code>CDF$new()</code></a></p></li>
<li><p><a href="/link/CDF%24plot()?package=LearnNonparam&version=1.2.7" data-mini-rdoc="LearnNonparam::CDF$plot()"><code>CDF$plot()</code></a></p></li>
</ul></p><p></p></div><p><details open><summary>Inherited methods</summary>
<ul>
<li><span class="pkg-link" data-pkg="LearnNonparam" data-topic="PermuTest" data-id="print"><a href="/link/LearnNonparam%3A%3APermuTest%24print()?package=LearnNonparam&version=1.2.7" data-mini-rdoc="LearnNonparam::LearnNonparam::PermuTest$print()"><code>LearnNonparam::PermuTest$print()</code></a></span></li>
<li><span class="pkg-link" data-pkg="LearnNonparam" data-topic="PermuTest" data-id="test"><a href="/link/LearnNonparam%3A%3APermuTest%24test()?package=LearnNonparam&version=1.2.7" data-mini-rdoc="LearnNonparam::LearnNonparam::PermuTest$test()"><code>LearnNonparam::PermuTest$test()</code></a></span></li>
</ul>
</details></p><p><hr>
<a id="method-CDF-new"></a></p><div class="section" id="method-new-">
<h3>Method <code>new()</code></h3>
<p>Create a new <code>CDF</code> object.</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>CDF$new(conf_level = 0.95)</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>conf_level</code></dt>
<dd><p>a number specifying confidence level of the confidence bounds.</p></dd></dl></div></p><p>
</p><p></p>

<div class="section" id="returns">
<h4>Returns</h4>
<p>A <code>CDF</code> object.</p>
</div><p></p><p></p><p><hr>
<a id="method-CDF-plot"></a></p><div class="section" id="method-plot-">
<h3>Method <code><a href="/link/plot()?package=LearnNonparam&version=1.2.7" data-mini-rdoc="LearnNonparam::plot()">plot()</a></code></h3>
<p>Plot the estimate and confidence bounds for population cumulative distribution function.</p><div class="section" id="usage">
<h4>Usage</h4>
<p><div class="r"></div></p><pre><code>CDF$plot(style = c("graphics", "ggplot2"))</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>style</code></dt>
<dd><p>a character string specifying which package to use.</p></dd></dl></div></p><p>
</p><p></p>

<div class="section" id="returns">
<h4>Returns</h4>
<p>The object itself (invisibly).</p>
</div><p></p><p>
</p>

Methods

Inference on Cumulative Distribution Function — CDF


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

<ul>
<li><p><a href='#method-CDF-new'><code>CDF$new()</code></a></p></li>
<li><p><a href='#method-CDF-plot'><code>CDF$plot()</code></a></p></li>
</ul>

</div><p><details open><summary>Inherited methods</summary>
<ul>
<li><span class="pkg-link" data-pkg="LearnNonparam" data-topic="PermuTest" data-id="print"><a href='../../LearnNonparam/html/PermuTest.html#method-PermuTest-print'><code>LearnNonparam::PermuTest$print()</code></a></span></li>
<li><span class="pkg-link" data-pkg="LearnNonparam" data-topic="PermuTest" data-id="test"><a href='../../LearnNonparam/html/PermuTest.html#method-PermuTest-test'><code>LearnNonparam::PermuTest$test()</code></a></span></li>
</ul>
</details>

<hr>
<a id="method-CDF-new"></a></p><div class='section' id='method-new-'>
<h3>Method <code>new()</code></h3>
<p>Create a new <code>CDF</code> object.</p><div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>CDF$new(conf_level = 0.95)</code></pre><p></div></p>
</div>

<div class='section' id='arguments'>
<h4>Arguments</h4>
<p><div class="arguments"></p><dl>
<dt><code>conf_level</code></dt>
<dd><p>a number specifying confidence level of the confidence bounds.</p></dd>


</dl><p></div></p>
</div>
<div class='section' id='returns'>
<h4>Returns</h4>
<p>A <code>CDF</code> object.</p>
</div>

</div><p><hr>
<a id="method-CDF-plot"></a></p><div class='section' id='method-plot-'>
<h3>Method <code><a href='https://rdrr.io/r/graphics/plot.default.html'>plot()</a></code></h3>
<p>Plot the estimate and confidence bounds for population cumulative distribution function.</p><div class='section' id='usage'>
<h4>Usage</h4>
<p><div class="r"></p><pre><code>CDF$plot(style = c("graphics", "ggplot2"))</code></pre><p></div></p>
</div>

<div class='section' id='arguments'>
<h4>Arguments</h4>
<p><div class="arguments"></p><dl>
<dt><code>style</code></dt>
<dd><p>a character string specifying which package to use.</p></dd>


</dl><p></div></p>
</div>
<div class='section' id='returns'>
<h4>Returns</h4>
<p>The object itself (invisibly).</p>
</div>

</div>


CDF: Inference on Cumulative Distribution Function

Description

Arguments

Super classes

Methods

Public methods

Method `new()`

Usage

Arguments

Returns

Method `plot()`

Usage

Arguments

Returns

Examples

Description

Arguments

Super classes

Methods

Public methods

Method new()

Usage

Arguments

Returns

Method plot()

Usage

Arguments

Returns

Examples

Method `new()`

Method `plot()`