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<h1>Plot calibration graphs from univariate linear models</h1>
<div class="hidden name"><code>calplot.lm.Rd</code></div>
</div>
<div class="ref-description">
<p>Produce graphics of calibration data, the fitted model as well
as confidence, and, for unweighted regression, prediction bands.</p>
</div>
<pre class="usage"><span class='fu'>calplot</span><span class='op'>(</span><span class='va'>object</span>, xlim <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"auto"</span>, <span class='st'>"auto"</span><span class='op'>)</span>, ylim <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"auto"</span>, <span class='st'>"auto"</span><span class='op'>)</span>,
xlab <span class='op'>=</span> <span class='st'>"Concentration"</span>, ylab <span class='op'>=</span> <span class='st'>"Response"</span>, legend_x <span class='op'>=</span> <span class='st'>"auto"</span>,
alpha<span class='op'>=</span><span class='fl'>0.05</span>, varfunc <span class='op'>=</span> <span class='cn'>NULL</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 univariate model object of class <code><a href='https://rdrr.io/r/stats/lm.html'>lm</a></code> or
<code><a href='https://rdrr.io/pkg/MASS/man/rlm.html'>rlm</a></code>
with model formula <code>y ~ x</code> or <code>y ~ x - 1</code>.</p></td>
</tr>
<tr>
<th>xlim</th>
<td><p>The limits of the plot on the x axis.</p></td>
</tr>
<tr>
<th>ylim</th>
<td><p>The limits of the plot on the y axis.</p></td>
</tr>
<tr>
<th>xlab</th>
<td><p>The label of the x axis.</p></td>
</tr>
<tr>
<th>ylab</th>
<td><p>The label of the y axis.</p></td>
</tr>
<tr>
<th>legend_x</th>
<td><p>An optional numeric value for adjusting the x coordinate of the legend.</p></td>
</tr>
<tr>
<th>alpha</th>
<td><p>The error tolerance level for the confidence and prediction bands. Note that this
includes both tails of the Gaussian distribution, unlike the alpha and beta parameters
used in <code><a href='lod.html'>lod</a></code> (see note below).</p></td>
</tr>
<tr>
<th>varfunc</th>
<td><p>The variance function for generating the weights in the model.
Currently, this argument is ignored (see note below).</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>A plot of the calibration data, of your fitted model as well as lines showing
the confidence limits. Prediction limits are only shown for models from
unweighted regression.</p>
<h2 class="hasAnchor" id="note"><a class="anchor" href="#note"></a>Note</h2>
<p>Prediction bands for models from weighted linear regression require weights
for the data, for which responses should be predicted. Prediction intervals
using weights e.g. from a variance function are currently not supported by
the internally used function <code><a href='https://rdrr.io/r/stats/predict.lm.html'>predict.lm</a></code>, therefore,
<code>calplot</code> does not draw prediction bands for such models.</p>
<p>It is possible to compare the <code>calplot</code> prediction bands with the
<code><a href='lod.html'>lod</a></code> values if the <code><a href='lod.html'>lod()</a></code> alpha and beta parameters are
half the value of the <code>calplot()</code> alpha parameter.</p>
<h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2>
<p>Johannes Ranke
<a href='mailto:jranke@uni-bremen.de'>jranke@uni-bremen.de</a></p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/utils/data.html'>data</a></span><span class='op'>(</span><span class='va'>massart97ex3</span><span class='op'>)</span>
<span class='va'>m</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/lm.html'>lm</a></span><span class='op'>(</span><span class='va'>y</span> <span class='op'>~</span> <span class='va'>x</span>, data <span class='op'>=</span> <span class='va'>massart97ex3</span><span class='op'>)</span>
<span class='fu'>calplot</span><span class='op'>(</span><span class='va'>m</span><span class='op'>)</span>
</div><div class='img'><img src='calplot.lm-1.png' alt='' width='700' height='433' /></div></pre>
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