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<h1>Calibration data from Massart et al. (1997), example 3</h1>
@@ -123,117 +55,123 @@
<p>Sample dataset from p. 188 to test the package.</p>
</div>
- <pre class="usage"><span class='va'>massart97ex3</span></pre>
-
-
- <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
+ <div id="ref-usage">
+ <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">massart97ex3</span></code></pre></div>
+ </div>
+ <div id="format">
+ <h2>Format</h2>
<p>A dataframe containing 6 levels of x values with 5
observations of y for each level.</p>
- <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
-
+ </div>
+ <div id="source">
+ <h2>Source</h2>
<p>Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J.,
Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A,
Chapter 8.</p>
+ </div>
- <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
- <pre class="examples"><div class='input'><span class='co'># For reproducing the results for replicate standard measurements in example 8,</span>
-<span class='co'># we need to do the calibration on the means when using chemCal &gt; 0.2</span>
-<span class='va'>weights</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/with.html'>with</a></span><span class='op'>(</span><span class='va'>massart97ex3</span>, <span class='op'>{</span>
- <span class='va'>yx</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/split.html'>split</a></span><span class='op'>(</span><span class='va'>y</span>, <span class='va'>x</span><span class='op'>)</span>
- <span class='va'>ybar</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>sapply</a></span><span class='op'>(</span><span class='va'>yx</span>, <span class='va'>mean</span><span class='op'>)</span>
- <span class='va'>s</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/Round.html'>round</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>sapply</a></span><span class='op'>(</span><span class='va'>yx</span>, <span class='va'>sd</span><span class='op'>)</span>, digits <span class='op'>=</span> <span class='fl'>2</span><span class='op'>)</span>
- <span class='va'>w</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/Round.html'>round</a></span><span class='op'>(</span><span class='fl'>1</span> <span class='op'>/</span> <span class='op'>(</span><span class='va'>s</span><span class='op'>^</span><span class='fl'>2</span><span class='op'>)</span>, digits <span class='op'>=</span> <span class='fl'>3</span><span class='op'>)</span>
-<span class='op'>}</span><span class='op'>)</span>
-
-<span class='va'>massart97ex3.means</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/stats/aggregate.html'>aggregate</a></span><span class='op'>(</span><span class='va'>y</span> <span class='op'>~</span> <span class='va'>x</span>, <span class='va'>massart97ex3</span>, <span class='va'>mean</span><span class='op'>)</span>
-
-<span class='va'>m3.means</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>, w <span class='op'>=</span> <span class='va'>weights</span>, data <span class='op'>=</span> <span class='va'>massart97ex3.means</span><span class='op'>)</span>
-
-<span class='co'># The following concords with the book p. 200</span>
-<span class='fu'><a href='inverse.predict.html'>inverse.predict</a></span><span class='op'>(</span><span class='va'>m3.means</span>, <span class='fl'>15</span>, ws <span class='op'>=</span> <span class='fl'>1.67</span><span class='op'>)</span> <span class='co'># 5.9 +- 2.5</span>
-</div><div class='output co'>#&gt; $Prediction
-#&gt; [1] 5.865367
-#&gt;
-#&gt; $`Standard Error`
-#&gt; [1] 0.8926109
-#&gt;
-#&gt; $Confidence
-#&gt; [1] 2.478285
-#&gt;
-#&gt; $`Confidence Limits`
-#&gt; [1] 3.387082 8.343652
-#&gt; </div><div class='input'><span class='fu'><a href='inverse.predict.html'>inverse.predict</a></span><span class='op'>(</span><span class='va'>m3.means</span>, <span class='fl'>90</span>, ws <span class='op'>=</span> <span class='fl'>0.145</span><span class='op'>)</span> <span class='co'># 44.1 +- 7.9</span>
-</div><div class='output co'>#&gt; $Prediction
-#&gt; [1] 44.06025
-#&gt;
-#&gt; $`Standard Error`
-#&gt; [1] 2.829162
-#&gt;
-#&gt; $Confidence
-#&gt; [1] 7.855012
-#&gt;
-#&gt; $`Confidence Limits`
-#&gt; [1] 36.20523 51.91526
-#&gt; </div><div class='input'>
-<span class='co'># The LOD is only calculated for models from unweighted regression</span>
-<span class='co'># with this version of chemCal</span>
-<span class='va'>m0</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'><a href='lod.html'>lod</a></span><span class='op'>(</span><span class='va'>m0</span><span class='op'>)</span>
-</div><div class='output co'>#&gt; $x
-#&gt; [1] 5.407085
-#&gt;
-#&gt; $y
-#&gt; [1] 13.63911
-#&gt; </div><div class='input'>
-<span class='co'># Limit of quantification from unweighted regression</span>
-<span class='fu'><a href='loq.html'>loq</a></span><span class='op'>(</span><span class='va'>m0</span><span class='op'>)</span>
-</div><div class='output co'>#&gt; $x
-#&gt; [1] 9.627349
-#&gt;
-#&gt; $y
-#&gt; [1] 22.00246
-#&gt; </div><div class='input'>
-<span class='co'># For calculating the limit of quantification from a model from weighted</span>
-<span class='co'># regression, we need to supply weights, internally used for inverse.predict</span>
-<span class='co'># If we are not using a variance function, we can use the weight from</span>
-<span class='co'># the above example as a first approximation (x = 15 is close to our</span>
-<span class='co'># loq approx 14 from above).</span>
-<span class='fu'><a href='loq.html'>loq</a></span><span class='op'>(</span><span class='va'>m3.means</span>, w.loq <span class='op'>=</span> <span class='fl'>1.67</span><span class='op'>)</span>
-</div><div class='output co'>#&gt; $x
-#&gt; [1] 7.346195
-#&gt;
-#&gt; $y
-#&gt; [1] 17.90777
-#&gt; </div><div class='input'><span class='co'># The weight for the loq should therefore be derived at x = 7.3 instead</span>
-<span class='co'># of 15, but the graphical procedure of Massart (p. 201) to derive the </span>
-<span class='co'># variances on which the weights are based is quite inaccurate anyway. </span>
-</div></pre>
+ <div id="ref-examples">
+ <h2>Examples</h2>
+ <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="co"># For reproducing the results for replicate standard measurements in example 8,</span></span>
+<span class="r-in"><span class="co"># we need to do the calibration on the means when using chemCal &gt; 0.2</span></span>
+<span class="r-in"><span class="va">weights</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/with.html" class="external-link">with</a></span><span class="op">(</span><span class="va">massart97ex3</span>, <span class="op">{</span></span>
+<span class="r-in"> <span class="va">yx</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/split.html" class="external-link">split</a></span><span class="op">(</span><span class="va">y</span>, <span class="va">x</span><span class="op">)</span></span>
+<span class="r-in"> <span class="va">ybar</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">yx</span>, <span class="va">mean</span><span class="op">)</span></span>
+<span class="r-in"> <span class="va">s</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">round</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/lapply.html" class="external-link">sapply</a></span><span class="op">(</span><span class="va">yx</span>, <span class="va">sd</span><span class="op">)</span>, digits <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span>
+<span class="r-in"> <span class="va">w</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/Round.html" class="external-link">round</a></span><span class="op">(</span><span class="fl">1</span> <span class="op">/</span> <span class="op">(</span><span class="va">s</span><span class="op">^</span><span class="fl">2</span><span class="op">)</span>, digits <span class="op">=</span> <span class="fl">3</span><span class="op">)</span></span>
+<span class="r-in"><span class="op">}</span><span class="op">)</span></span>
+<span class="r-in"></span>
+<span class="r-in"><span class="va">massart97ex3.means</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/aggregate.html" class="external-link">aggregate</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, <span class="va">massart97ex3</span>, <span class="va">mean</span><span class="op">)</span></span>
+<span class="r-in"></span>
+<span class="r-in"><span class="va">m3.means</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>, w <span class="op">=</span> <span class="va">weights</span>, data <span class="op">=</span> <span class="va">massart97ex3.means</span><span class="op">)</span></span>
+<span class="r-in"></span>
+<span class="r-in"><span class="co"># The following concords with the book p. 200</span></span>
+<span class="r-in"><span class="fu"><a href="inverse.predict.html">inverse.predict</a></span><span class="op">(</span><span class="va">m3.means</span>, <span class="fl">15</span>, ws <span class="op">=</span> <span class="fl">1.67</span><span class="op">)</span> <span class="co"># 5.9 +- 2.5</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $Prediction</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 5.865367</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $`Standard Error`</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.8926109</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $Confidence</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 2.478285</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $`Confidence Limits`</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 3.387082 8.343652</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-in"><span class="fu"><a href="inverse.predict.html">inverse.predict</a></span><span class="op">(</span><span class="va">m3.means</span>, <span class="fl">90</span>, ws <span class="op">=</span> <span class="fl">0.145</span><span class="op">)</span> <span class="co"># 44.1 +- 7.9</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $Prediction</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 44.06025</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $`Standard Error`</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 2.829162</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $Confidence</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 7.855012</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $`Confidence Limits`</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 36.20523 51.91526</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-in"></span>
+<span class="r-in"><span class="co"># The LOD is only calculated for models from unweighted regression</span></span>
+<span class="r-in"><span class="co"># with this version of chemCal</span></span>
+<span class="r-in"><span class="va">m0</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"><a href="lod.html">lod</a></span><span class="op">(</span><span class="va">m0</span><span class="op">)</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $x</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 5.407085</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $y</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 13.63911</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-in"></span>
+<span class="r-in"><span class="co"># Limit of quantification from unweighted regression</span></span>
+<span class="r-in"><span class="fu"><a href="loq.html">loq</a></span><span class="op">(</span><span class="va">m0</span><span class="op">)</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $x</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 9.627349</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $y</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 22.00246</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-in"></span>
+<span class="r-in"><span class="co"># For calculating the limit of quantification from a model from weighted</span></span>
+<span class="r-in"><span class="co"># regression, we need to supply weights, internally used for inverse.predict</span></span>
+<span class="r-in"><span class="co"># If we are not using a variance function, we can use the weight from</span></span>
+<span class="r-in"><span class="co"># the above example as a first approximation (x = 15 is close to our</span></span>
+<span class="r-in"><span class="co"># loq approx 14 from above).</span></span>
+<span class="r-in"><span class="fu"><a href="loq.html">loq</a></span><span class="op">(</span><span class="va">m3.means</span>, w.loq <span class="op">=</span> <span class="fl">1.67</span><span class="op">)</span></span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $x</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 7.346195</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> $y</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> [1] 17.90777</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-in"><span class="co"># The weight for the loq should therefore be derived at x = 7.3 instead</span></span>
+<span class="r-in"><span class="co"># of 15, but the graphical procedure of Massart (p. 201) to derive the </span></span>
+<span class="r-in"><span class="co"># variances on which the weights are based is quite inaccurate anyway. </span></span>
+</code></pre></div>
+ </div>
</div>
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