Use 'investr' conditionally in tests, updates

Most prominently, a README was added, giving a nice overview for the people visiting the github page, the package page on CRAN, or the online docs at pkgdown.jrwb.de. The maintainer e-mail address was also updated.
author: Johannes Ranke <jranke@uni-bremen.de> 2022-03-23 10:32:36 +0100
committer: Johannes Ranke <jranke@uni-bremen.de> 2022-03-31 18:35:09 +0200
commit: f4fcef8228ebd5a1a73bc6edc47b5efa259c2e20 (patch)
tree: f9e0489c8941257b5055783a443f4859212ad4f1 /docs/reference/calplot.lm.html
parent: 4c2b22d75cc5102ddc595ea479c46bfdb46c1016 (diff)
1 files changed, 68 insertions, 150 deletions
diff --git a/docs/reference/calplot.lm.html b/docs/reference/calplot.lm.html
index b041a8d..7865a66 100644
--- a/docs/reference/calplot.lm.html
+++ b/docs/reference/calplot.lm.html
@@ -1,68 +1,13 @@
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@@ -73,19 +18,12 @@
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         <a class="navbar-link" href="../index.html">chemCal</a>
-        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.2.2</span>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.2.3</span>
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@@ -94,25 +32,19 @@
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-      <ul class="nav navbar-nav navbar-right">
-        <li>
-  <a href="https://github.com/jranke/chemCal/">
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+      </header><div class="row">
   <div class="col-md-9 contents">
     <div class="page-header">
     <h1>Plot calibration graphs from univariate linear models</h1>
@@ -125,102 +57,88 @@
   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>
+    <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>
-    <h2 class="hasAnchor" id="note"><a class="anchor" href="#note"></a>Note</h2>
-
+    </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'>predict.lm</a></code>, therefore,
+  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
+  <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>
-
+    </div>
+    <div id="author">
+    <h2>Author</h2>
     <p>Johannes Ranke 
-  <a href='mailto:jranke@uni-bremen.de'>jranke@uni-bremen.de</a></p>
+  <a href="mailto:jranke@uni-bremen.de">jranke@uni-bremen.de</a></p>
+    </div>
 
-    <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'>&lt;-</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>
+    <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">&lt;-</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>
   </div>
   <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
-    <nav id="toc" data-toggle="toc" class="sticky-top">
-      <h2 data-toc-skip>Contents</h2>
-    </nav>
-  </div>
+    <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2>
+    </nav></div>
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+  <p></p><p>Developed by Johannes Ranke.</p>
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+  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p>
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author	Johannes Ranke <jranke@uni-bremen.de>	2022-03-23 10:32:36 +0100
committer	Johannes Ranke <jranke@uni-bremen.de>	2022-03-31 18:35:09 +0200
commit	f4fcef8228ebd5a1a73bc6edc47b5efa259c2e20 (patch)
tree	f9e0489c8941257b5055783a443f4859212ad4f1 /docs/reference/calplot.lm.html
parent	4c2b22d75cc5102ddc595ea479c46bfdb46c1016 (diff)