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<title>calplot. chemCal 0.1-35.900</title>
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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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<h1>Plot calibration graphs from univariate linear models</h1>
<div class="row">
<div class="span8">
<h2>Usage</h2>
<pre><div>calplot(object, xlim = c("auto", "auto"), ylim = c("auto", "auto"), xlab = "Concentration", ylab = "Response", alpha=0.05, varfunc = NULL)</div></pre>
<h2>Arguments</h2>
<dl>
<dt>object</dt>
<dd>
A univariate model object of class <code><a href='http://www.inside-r.org/r-doc/stats/lm'>lm</a></code> or
<code><a href='http://www.inside-r.org/r-doc/MASS/rlm'>rlm</a></code>
with model formula <code>y ~ x</code> or <code>y ~ x - 1</code>.
</dd>
<dt>xlim</dt>
<dd>
The limits of the plot on the x axis.
</dd>
<dt>ylim</dt>
<dd>
The limits of the plot on the y axis.
</dd>
<dt>xlab</dt>
<dd>
The label of the x axis.
</dd>
<dt>ylab</dt>
<dd>
The label of the y axis.
</dd>
<dt>alpha</dt>
<dd>
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).
</dd>
<dt>varfunc</dt>
<dd>
The variance function for generating the weights in the model.
Currently, this argument is ignored (see note below).
</dd>
</dl>
<div class="Description">
<h2>Description</h2>
<p>Produce graphics of calibration data, the fitted model as well
as confidence, and, for unweighted regression, prediction bands.</p>
</div>
<div class="Value">
<h2>Value</h2>
<p><dl>
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.
</dl></p>
</div>
<div class="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='http://www.inside-r.org/r-doc/stats/predict.lm'>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><a href='calplot.lm.html'>calplot</a></code> prediction bands with the
<code><a href='lod.html'>lod</a></code> values if the <code>lod()</code> alpha and beta parameters are
half the value of the <code>calplot()</code> alpha parameter.</p>
<p></p>
</div>
<h2 id="examples">Examples</h2>
<pre class="examples"><div class='input'>data(massart97ex3)
m <- lm(y ~ x, data = massart97ex3)
calplot(m)
</div>
<p><img src='calplot.lm-2.png' alt='' width='540' height='400' /></p></pre>
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<li>calplot</li><li>calplot.default</li><li>calplot.lm</li>
</ul>
<ul>
<li>regression</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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