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as confidence, and, for unweighted regression, prediction bands."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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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>
<div id="ref-usage">
<div class="sourceCode"><pre class="sourceCode r"><code><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" class="external-link">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" class="external-link">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></code></pre></div>
</div>
<div id="arguments">
<h2>Arguments</h2>
<dl><dt>object</dt>
<dd><p>A univariate model object of class <code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></code> or
<code><a href="https://rdrr.io/pkg/MASS/man/rlm.html" class="external-link">rlm</a></code>
with model formula <code>y ~ x</code> or <code>y ~ x - 1</code>.</p></dd>
<dt>xlim</dt>
<dd><p>The limits of the plot on the x axis.</p></dd>
<dt>ylim</dt>
<dd><p>The limits of the plot on the y axis.</p></dd>
<dt>xlab</dt>
<dd><p>The label of the x axis.</p></dd>
<dt>ylab</dt>
<dd><p>The label of the y axis.</p></dd>
<dt>legend_x</dt>
<dd><p>An optional numeric value for adjusting the x coordinate of the legend.</p></dd>
<dt>alpha</dt>
<dd><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></dd>
<dt>varfunc</dt>
<dd><p>The variance function for generating the weights in the model.
Currently, this argument is ignored (see note below).</p></dd>
</dl></div>
<div id="value">
<h2>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>
</div>
<div id="note">
<h2>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" class="external-link">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>
</div>
<div id="author">
<h2>Author</h2>
<p>Johannes Ranke
<a href="mailto:jranke@uni-bremen.de">jranke@uni-bremen.de</a></p>
</div>
<div id="ref-examples">
<h2>Examples</h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="fu"><a href="https://rdrr.io/r/utils/data.html" class="external-link">data</a></span><span class="op">(</span><span class="va">massart97ex3</span><span class="op">)</span></span>
<span class="r-in"><span class="va">m</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">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>
<span class="r-in"><span class="fu">calplot</span><span class="op">(</span><span class="va">m</span><span class="op">)</span></span>
<span class="r-plt img"><img src="calplot.lm-1.png" alt="" width="700" height="433"></span>
</code></pre></div>
</div>
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