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+\name{din32645}
+\docType{data}
+\alias{din32645}
+\title{Calibration data from DIN 32645}
+\description{
+ Sample dataset to test the package.
+}
+\usage{data(din32645)}
+\format{
+ A dataframe containing 10 rows of x and y values.
+}
+\examples{
+data(din32645)
+m <- lm(y ~ x, data = din32645)
+calplot(m)
+
+## Prediction of x with confidence interval
+(prediction <- inverse.predict(m, 3500, alpha = 0.01))
+
+# 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$Confidence,5)
+
+## Critical value:
+(crit <- lod(m, alpha = 0.01, beta = 0.5))
+
+# According to DIN 32645, we should get 0.07 for the critical value
+# (decision limit, "Nachweisgrenze")
+round(crit$x, 2)
+# and according to Dintest test data, we should get 0.0698 from
+round(crit$x, 4)
+
+## Limit of detection (smallest detectable value given alpha and beta)
+# In German, the smallest detectable value is the "Erfassungsgrenze", and we
+# should get 0.14 according to DIN, which we achieve by using the method
+# described in it:
+lod.din <- lod(m, alpha = 0.01, beta = 0.01, method = "din")
+round(lod.din$x, 2)
+
+## 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 <- loq(m, alpha = 0.01))
+round(loq$x,4)
+
+# A similar value is obtained using the approximation
+# LQ = 3.04 * LC (Currie 1999, p. 120)
+3.04 * lod(m,alpha = 0.01, beta = 0.5)$x
+}
+\references{
+ DIN 32645 (equivalent to ISO 11843), Beuth Verlag, Berlin, 1994
+
+ Dintest. Plugin for MS Excel for evaluations of calibration data. Written
+ by Georg Schmitt, University of Heidelberg.
+ \url{http://www.rzuser.uni-heidelberg.de/~df6/download/dintest.htm}
+
+ Currie, L. A. (1997) Nomenclature in evaluation of analytical methods including
+ detection and quantification capabilities (IUPAC Recommendations 1995).
+ Analytica Chimica Acta 391, 105 - 126.
+}
+\keyword{datasets}

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