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- <h1>Calibration data from DIN 32645</h1>
-
-<div class="row">
- <div class="span8">
- <h2>Usage</h2>
- <pre><div>data(din32645)</div></pre>
-
- <div class="Description">
- <h2>Description</h2>
-
- <p>Sample dataset to test the package.</p>
-
- </div>
-
- <div class="Format">
- <h2>Format</h2>
-
- <p>A dataframe containing 10 rows of x and y values.</p>
-
- </div>
-
- <div class="References">
- <h2>References</h2>
-
- <p>DIN 32645 (equivalent to ISO 11843), Beuth Verlag, Berlin, 1994</p>
-
- <p>Dintest. Plugin for MS Excel for evaluations of calibration data. Written
- by Georg Schmitt, University of Heidelberg. Formerly available from
- the Website of the University of Heidelberg.</p>
-
- <p>Currie, L. A. (1997) Nomenclature in evaluation of analytical methods including
- detection and quantification capabilities (IUPAC Recommendations 1995).
- Analytica Chimica Acta 391, 105 - 126.</p>
-
- </div>
-
- <h2 id="examples">Examples</h2>
- <pre class="examples"><div class='input'>data(din32645)
-m &lt;- lm(y ~ x, data = din32645)
-calplot(m)
-</div>
-<p><img src='din32645-2.png' alt='' width='540' height='400' /></p>
-<div class='input'>
-## Prediction of x with confidence interval
-(prediction &lt;- inverse.predict(m, 3500, alpha = 0.01))
-</div>
-<div class='output'>$Prediction
-[1] 0.1054792
-
-$`Standard Error`
-[1] 0.02215619
-
-$Confidence
-[1] 0.07434261
-
-$`Confidence Limits`
-[1] 0.03113656 0.17982178
-
-</div>
-<div class='input'>
-# This should give 0.07434 according to test data from Dintest, which
-# was collected from Procontrol 3.1 (isomehr GmbH) in this case
-round(prediction$Confidence,5)
-</div>
-<div class='output'>[1] 0.07434
-</div>
-<div class='input'>
-## Critical value:
-(crit &lt;- lod(m, alpha = 0.01, beta = 0.5))
-</div>
-<div class='output'>$x
-[1] 0.0698127
-
-$y
- 1
-3155.393
-
-</div>
-<div class='input'>
-# According to DIN 32645, we should get 0.07 for the critical value
-# (decision limit, &quot;Nachweisgrenze&quot;)
-round(crit$x, 2)
-</div>
-<div class='output'>[1] 0.07
-</div>
-<div class='input'># and according to Dintest test data, we should get 0.0698 from
-round(crit$x, 4)
-</div>
-<div class='output'>[1] 0.0698
-</div>
-<div class='input'>
-## Limit of detection (smallest detectable value given alpha and beta)
-# In German, the smallest detectable value is the &quot;Erfassungsgrenze&quot;, and we
-# should get 0.14 according to DIN, which we achieve by using the method
-# described in it:
-lod.din &lt;- lod(m, alpha = 0.01, beta = 0.01, method = &quot;din&quot;)
-round(lod.din$x, 2)
-</div>
-<div class='output'>[1] 0.14
-</div>
-<div class='input'>
-## Limit of quantification
-# This accords to the test data coming with the test data from Dintest again,
-# except for the last digits of the value cited for Procontrol 3.1 (0.2121)
-(loq &lt;- loq(m, alpha = 0.01))
-</div>
-<div class='output'>$x
-[1] 0.2119575
-
-$y
- 1
-4528.787
-
-</div>
-<div class='input'>round(loq$x,4)
-</div>
-<div class='output'>[1] 0.212
-</div>
-<div class='input'>
-# A similar value is obtained using the approximation
-# LQ = 3.04 * LC (Currie 1999, p. 120)
-3.04 * lod(m,alpha = 0.01, beta = 0.5)$x
-</div>
-<div class='output'>[1] 0.2122306
-</div></pre>
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