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vine_methods.html
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vine_methods.html
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<h1>Vine based distributions</h1>
<small class="dont-index">Source: <a href='https://github.com/vinecopulib/rvinecopulib/blob/master/R/vine_methods.R'><code>R/vine_methods.R</code></a></small>
<div class="hidden name"><code>vine_methods.Rd</code></div>
</div>
<div class="ref-description">
<p>Density, distribution function and random generation
for the vine based distribution.</p>
</div>
<pre class="usage"><span class='fu'>dvine</span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>vine</span>, cores <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span>
<span class='fu'>pvine</span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>vine</span>, n_mc <span class='op'>=</span> <span class='fl'>10</span><span class='op'>^</span><span class='fl'>4</span>, cores <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span>
<span class='fu'>rvine</span><span class='op'>(</span><span class='va'>n</span>, <span class='va'>vine</span>, qrng <span class='op'>=</span> <span class='cn'>FALSE</span>, cores <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span></pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>evaluation points, either a length d vector or a d-column matrix,
where d is the number of variables in the vine.</p></td>
</tr>
<tr>
<th>vine</th>
<td><p>an object of class <code>"vine_dist"</code>.</p></td>
</tr>
<tr>
<th>cores</th>
<td><p>number of cores to use; if larger than one, computations are
done in parallel on <code>cores</code> batches .</p></td>
</tr>
<tr>
<th>n_mc</th>
<td><p>number of samples used for quasi Monte Carlo integration.</p></td>
</tr>
<tr>
<th>n</th>
<td><p>number of observations.</p></td>
</tr>
<tr>
<th>qrng</th>
<td><p>if <code>TRUE</code>, generates quasi-random numbers using the multivariate
Generalized Halton sequence up to dimension 300 and the Generalized Sobol
sequence in higher dimensions (default <code>qrng = FALSE</code>).</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p><code>dvine()</code> gives the density, <code>pvine()</code> gives the distribution function,
and <code>rvine()</code> generates random deviates.</p>
<p>The length of the result is determined by <code>n</code> for <code>rvine()</code>, and
the number of rows in <code>u</code> for the other functions.</p>
<p>The <code>vine</code> object is recycled to the length of the
result.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>See <a href='vine.html'>vine</a> for the estimation and construction of vine models.
Here, the density, distribution function and random generation
for the vine distributions are standard.</p>
<p>The functions are based on <code><a href='vinecop_distributions.html'>dvinecop()</a></code>, <code><a href='vinecop_distributions.html'>pvinecop()</a></code> and <code><a href='vinecop_distributions.html'>rvinecop()</a></code> for
<a href='vinecop.html'>vinecop</a> objects, and either <code><a href='https://rdrr.io/pkg/kde1d/man/dkde1d.html'>kde1d::dkde1d()</a></code>, <code><a href='https://rdrr.io/pkg/kde1d/man/dkde1d.html'>kde1d::pkde1d()</a></code> and
<code><a href='https://rdrr.io/pkg/kde1d/man/dkde1d.html'>kde1d::qkde1d()</a></code> for estimated vines (i.e., output of <code><a href='vine.html'>vine()</a></code>), or the
standard <em>d/p/q-xxx</em> from <a href='https://rdrr.io/r/stats/Distributions.html'>stats::Distributions</a> for custom vines
(i.e., output of <code><a href='vine.html'>vine_dist()</a></code>).</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># specify pair-copulas</span>
<span class='va'>bicop</span> <span class='op'><-</span> <span class='fu'><a href='bicop_dist.html'>bicop_dist</a></span><span class='op'>(</span><span class='st'>"bb1"</span>, <span class='fl'>90</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>3</span>, <span class='fl'>2</span><span class='op'>)</span><span class='op'>)</span>
<span class='va'>pcs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>
<span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='va'>bicop</span>, <span class='va'>bicop</span><span class='op'>)</span>, <span class='co'># pair-copulas in first tree</span>
<span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='va'>bicop</span><span class='op'>)</span> <span class='co'># pair-copulas in second tree</span>
<span class='op'>)</span>
<span class='co'># set up vine copula model</span>
<span class='va'>mat</span> <span class='op'><-</span> <span class='fu'><a href='rvine_structure_sim.html'>rvine_matrix_sim</a></span><span class='op'>(</span><span class='fl'>3</span><span class='op'>)</span>
<span class='va'>vc</span> <span class='op'><-</span> <span class='fu'><a href='vine.html'>vine_dist</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>distr <span class='op'>=</span> <span class='st'>"norm"</span><span class='op'>)</span>, <span class='va'>pcs</span>, <span class='va'>mat</span><span class='op'>)</span>
<span class='co'># simulate from the model</span>
<span class='va'>x</span> <span class='op'><-</span> <span class='fu'>rvine</span><span class='op'>(</span><span class='fl'>200</span>, <span class='va'>vc</span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/r/graphics/pairs.html'>pairs</a></span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span>
</div><div class='img'><img src='vine_methods-1.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='co'># evaluate the density and cdf</span>
<span class='fu'>dvine</span><span class='op'>(</span><span class='va'>x</span><span class='op'>[</span><span class='fl'>1</span>, <span class='op'>]</span>, <span class='va'>vc</span><span class='op'>)</span>
</div><div class='output co'>#> [1] 0.2299133</div><div class='input'><span class='fu'>pvine</span><span class='op'>(</span><span class='va'>x</span><span class='op'>[</span><span class='fl'>1</span>, <span class='op'>]</span>, <span class='va'>vc</span><span class='op'>)</span>
</div><div class='output co'>#> [1] 0.0017</div></pre>
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