From 764531edb7c5598c7b1e401d6e2028ec832db1c4 Mon Sep 17 00:00:00 2001
From: Johannes Ranke <jranke@uni-bremen.de>
Date: Tue, 17 Jul 2018 19:24:17 +0200
Subject: Canonicalize link into bug tracking system

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 <a href="#basic-calibration-functions" class="anchor"></a>Basic calibration functions</h1>
 <p>The <code>chemCal</code> package was first designed in the course of a lecture and lab course on “Analytics of Organic Trace Contaminants” at the University of Bremen from October to December 2004. In the fall 2005, an email exchange with Ron Wehrens led to the belief that it would be desirable to implement the inverse prediction method given in <span class="citation">Massart et al. (1997)</span> since it also covers the case of weighted regression. Studies of the IUPAC orange book and of DIN 32645 (equivalent to ISO 11843), publications by <span class="citation">Currie (1997)</span> and the Analytical Method Committee of the Royal Society of Chemistry <span class="citation">(Analytical Methods Committee 1989)</span> and a nice paper by Castells and Castillo <span class="citation">(Castells and Castillo 2000)</span> provided some further understanding of the matter.</p>
 <p>At the moment, the package consists of four functions (<a href="https://pkgdown.jrwb.de/chemCal/reference/calplot.lm.html">calplot</a>, <a href="https://pkgdown.jrwb.de/chemCal/reference/lod.html">lod</a>, <a href="https://pkgdown.jrwb.de/chemCal/reference/loq.html">loq</a> and <a href="https://pkgdown.jrwb.de/chemCal/reference/inverse.predict.html">inverse.predict</a>), working on univariate linear models of class <code>lm</code> or <code>rlm</code>, plus several datasets for validation.</p>
-<p>A <a href="http://bugs.r-project.org/bugzilla3/show_bug.cgi?id=8877">bug report</a> and the following e-mail exchange on the r-devel mailing list about prediction intervals from weighted regression entailed some further studies on this subject. However, I did not encounter any proof or explanation of the formula cited below yet, so I can’t really confirm that Massart’s method is correct.</p>
+<p>A <a href="https://bugs.r-project.org/bugzilla/show_bug.cgi?id=8877">bug report</a> and the following e-mail exchange on the r-devel mailing list about prediction intervals from weighted regression entailed some further studies on this subject. However, I did not encounter any proof or explanation of the formula cited below yet, so I can’t really confirm that Massart’s method is correct.</p>
 <p>In fact, in June 2018 I was made aware of the fact that the inverse prediction method implemented in chemCal version 0.1.37 and before did not take the variance of replicate calibration standards about their means into account, nor the number of replicates when calculating the degrees of freedom. Thanks to PhD student Anna Burniol Figols for reporting this issue!</p>
 <p>As a consequence, I rewrote <code>inverse.predict</code> not to automatically work with the mean responses for each calibration standard any more. The example calculations from <span class="citation">Massart et al. (1997)</span> can still be reproduced when the regression model is calculated using the means of the calibration data as shown below.</p>
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