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<h1>Plot calibration graphs from univariate linear models</h1>
</div>
<p>Produce graphics of calibration data, the fitted model as well
as confidence, and, for unweighted regression, prediction bands.</p>
<pre class="usage"><span class='fu'>calplot</span>(<span class='no'>object</span>, <span class='kw'>xlim</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='st'>"auto"</span>, <span class='st'>"auto"</span>), <span class='kw'>ylim</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='st'>"auto"</span>, <span class='st'>"auto"</span>),
<span class='kw'>xlab</span> <span class='kw'>=</span> <span class='st'>"Concentration"</span>, <span class='kw'>ylab</span> <span class='kw'>=</span> <span class='st'>"Response"</span>, <span class='kw'>alpha</span><span class='kw'>=</span><span class='fl'>0.05</span>, <span class='kw'>varfunc</span> <span class='kw'>=</span> <span class='kw'>NULL</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>lm</code> or
<code><a href='http://www.rdocumentation.org/packages/MASS/topics/rlm'>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>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>lod</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>predict.lm</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>lod</code> values if the <code>lod()</code> alpha and beta parameters are
half the value of the <code>calplot()</code> alpha parameter.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='fu'>data</span>(<span class='no'>massart97ex3</span>)
<span class='no'>m</span> <span class='kw'><-</span> <span class='fu'>lm</span>(<span class='no'>y</span> ~ <span class='no'>x</span>, <span class='kw'>data</span> <span class='kw'>=</span> <span class='no'>massart97ex3</span>)
<span class='fu'>calplot</span>(<span class='no'>m</span>)</div><div class='img'><img src='calplot.lm-1.png' alt='' width='700' height='432.632880098887' /></div></pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#note">Note</a></li>
<li><a href="#examples">Examples</a></li>
</ul>
<h2>Author</h2>
Johannes Ranke
<a href='mailto:jranke@uni-bremen.de'>jranke@uni-bremen.de</a>
<a href='http://www.uft.uni-bremen.de/chemie/ranke'>http://www.uft.uni-bremen.de/chemie/ranke</a>
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