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predict_vinecop.html
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predict_vinecop.html
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<h1>Predictions and fitted values for a vine copula model</h1>
<small class="dont-index">Source: <a href='https://github.com/vinecopulib/rvinecopulib/blob/master/R/vinecop_methods.R'><code>R/vinecop_methods.R</code></a></small>
<div class="hidden name"><code>predict_vinecop.Rd</code></div>
</div>
<div class="ref-description">
<p>Predictions of the density and distribution function
for a vine copula model.</p>
</div>
<pre class="usage"><span class='co'># S3 method for vinecop</span>
<span class='fu'><a href='https://rdrr.io/r/stats/predict.html'>predict</a></span><span class='op'>(</span><span class='va'>object</span>, <span class='va'>newdata</span>, what <span class='op'>=</span> <span class='st'>"pdf"</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='va'>...</span><span class='op'>)</span>
<span class='co'># S3 method for vinecop</span>
<span class='fu'><a href='https://rdrr.io/r/stats/fitted.values.html'>fitted</a></span><span class='op'>(</span><span class='va'>object</span>, what <span class='op'>=</span> <span class='st'>"pdf"</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='va'>...</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>object</th>
<td><p>a <code>vinecop</code> object.</p></td>
</tr>
<tr>
<th>newdata</th>
<td><p>points where the fit shall be evaluated.</p></td>
</tr>
<tr>
<th>what</th>
<td><p>what to predict, either <code>"pdf"</code> or <code>"cdf"</code>.</p></td>
</tr>
<tr>
<th>n_mc</th>
<td><p>number of samples used for quasi Monte Carlo integration when
<code>what = "cdf"</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>...</th>
<td><p>unused.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p><code><a href='https://rdrr.io/r/stats/fitted.values.html'>fitted()</a></code> and <code><a href='https://rdrr.io/r/stats/predict.html'>predict()</a></code> have return values similar to <code><a href='vinecop_distributions.html'>dvinecop()</a></code>
and <code><a href='vinecop_distributions.html'>pvinecop()</a></code>.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p><code><a href='https://rdrr.io/r/stats/fitted.values.html'>fitted()</a></code> can only be called if the model was fit with the
<code>keep_data = TRUE</code> option.</p><h3 class='hasAnchor' id='arguments'><a class='anchor' href='#arguments'></a>Discrete variables</h3>
<p>When at least one variable is discrete, two types of
"observations" are required in <code>newdata</code>: the first \(n \; x \; d\) block
contains realizations of \(F_{X_j}(X_j)\). The second \(n \; x \; d\)
block contains realizations of \(F_{X_j}(X_j^-)\). The minus indicates a
left-sided limit of the cdf. For, e.g., an integer-valued variable, it holds
\(F_{X_j}(X_j^-) = F_{X_j}(X_j - 1)\). For continuous variables the left
limit and the cdf itself coincide. Respective columns can be omitted in the
second block.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='va'>u</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>sapply</a></span><span class='op'>(</span><span class='fl'>1</span><span class='op'>:</span><span class='fl'>5</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>i</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/stats/Uniform.html'>runif</a></span><span class='op'>(</span><span class='fl'>50</span><span class='op'>)</span><span class='op'>)</span>
<span class='va'>fit</span> <span class='op'><-</span> <span class='fu'><a href='vinecop.html'>vinecop</a></span><span class='op'>(</span><span class='va'>u</span>, family <span class='op'>=</span> <span class='st'>"par"</span>, keep_data <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/r/base/all.equal.html'>all.equal</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/stats/predict.html'>predict</a></span><span class='op'>(</span><span class='va'>fit</span>, <span class='va'>u</span><span class='op'>)</span>, <span class='fu'><a href='https://rdrr.io/r/stats/fitted.values.html'>fitted</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span>, check.environment <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>
</div><div class='output co'>#> [1] TRUE</div></pre>
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